pgBadger-
Global information
- Generated on Mon Mar 31 03:59:50 2025
- Log file: /home/postgres/pg_data/data/pg_log/postgresql-2025-03-31_050000.log
- Parsed 1,576,675 log entries in 49s
- Log start from 2025-03-31 05:00:00 to 2025-03-31 05:59:47
-
Overview
Global Stats
- 202 Number of unique normalized queries
- 108,997 Number of queries
- 2h2m45s Total query duration
- 2025-03-31 05:00:00 First query
- 2025-03-31 05:59:47 Last query
- 2,609 queries/s at 2025-03-31 05:30:10 Query peak
- 2h2m45s Total query duration
- 7s695ms Prepare/parse total duration
- 1m16s Bind total duration
- 2h1m21s Execute total duration
- 23 Number of events
- 1 Number of unique normalized events
- 23 Max number of times the same event was reported
- 0 Number of cancellation
- 39 Total number of automatic vacuums
- 59 Total number of automatic analyzes
- 489 Number temporary file
- 130.76 MiB Max size of temporary file
- 6.97 MiB Average size of temporary file
- 3,348 Total number of sessions
- 21 sessions at 2025-03-31 05:56:13 Session peak
- 3d13h29m16s Total duration of sessions
- 1m31s Average duration of sessions
- 32 Average queries per session
- 2s200ms Average queries duration per session
- 1m29s Average idle time per session
- 3,348 Total number of connections
- 39 connections/s at 2025-03-31 05:00:03 Connection peak
- 2 Total number of databases
SQL Traffic
Key values
- 2,609 queries/s Query Peak
- 2025-03-31 05:30:10 Date
SELECT Traffic
Key values
- 2,137 queries/s Query Peak
- 2025-03-31 05:30:04 Date
INSERT/UPDATE/DELETE Traffic
Key values
- 2,030 queries/s Query Peak
- 2025-03-31 05:30:10 Date
Queries duration
Key values
- 2h2m45s Total query duration
Prepared queries ratio
Key values
- 0.00 Ratio of bind vs prepare
- 0.00 % Ratio between prepared and "usual" statements
General Activity
↑ Back to the top of the General Activity tableDay Hour Count Min duration Max duration Avg duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Mar 31 05 108,997 0ms 38s424ms 66ms 3m22s 3m46s 4m5s Day Hour SELECT COPY TO Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Mar 31 05 69,234 26 2ms 4s202ms 12s929ms 14s959ms Day Hour INSERT UPDATE DELETE COPY FROM Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Mar 31 05 25,795 2,447 16 96 1ms 655ms 1s108ms 2s749ms Day Hour Prepare Bind Bind/Prepare Percentage of prepare Mar 31 05 28,847 94,296 3.27 27.10% Day Hour Count Average / Second Mar 31 05 3,348 0.93/s Day Hour Count Average Duration Average idle time Mar 31 05 3,348 1m31s 1m29s -
Connections
Established Connections
Key values
- 39 connections Connection Peak
- 2025-03-31 05:00:03 Date
Connections per database
Key values
- acaweb_fx Main Database
- 3,348 connections Total
Connections per user
Key values
- postgres Main User
- 3,348 connections Total
Connections per host
Key values
- 192.168.4.142 Main host with 1171 connections
- 3,348 Total connections
Host Count 127.0.0.1 124 182.165.1.42 4 192.168.0.114 8 192.168.0.216 100 192.168.1.145 135 192.168.1.20 157 192.168.1.23 556 192.168.1.239 12 192.168.1.250 103 192.168.1.90 52 192.168.2.126 62 192.168.2.182 12 192.168.2.205 12 192.168.2.82 47 192.168.3.199 63 192.168.4.142 1,171 192.168.4.150 10 192.168.4.238 18 192.168.4.27 6 192.168.4.33 91 192.168.4.35 1 192.168.4.98 330 [local] 274 -
Sessions
Simultaneous sessions
Key values
- 21 sessions Session Peak
- 2025-03-31 05:56:13 Date
Histogram of session times
Key values
- 2,649 0-500ms duration
Sessions per database
Key values
- acaweb_fx Main Database
- 3,348 sessions Total
Sessions per user
Key values
- postgres Main User
- 3,348 sessions Total
Sessions per host
Key values
- 192.168.4.142 Main Host
- 3,348 sessions Total
Host Count Total Duration Average Duration 127.0.0.1 124 1h46s 29s403ms 182.165.1.42 4 35m57s 8m59s 192.168.0.114 8 11h59m15s 1h29m54s 192.168.0.216 100 42s626ms 426ms 192.168.1.145 135 4h4m12s 1m48s 192.168.1.20 157 1d6h55m24s 11m49s 192.168.1.23 556 1h52m53s 12s182ms 192.168.1.239 12 120ms 10ms 192.168.1.250 103 14h34m10s 8m29s 192.168.1.90 52 35s64ms 674ms 192.168.2.126 62 6s456ms 104ms 192.168.2.182 12 736ms 61ms 192.168.2.205 12 1s311ms 109ms 192.168.2.82 47 10s422ms 221ms 192.168.3.199 63 36s735ms 583ms 192.168.4.142 1,171 14m44s 755ms 192.168.4.150 10 20h6m40s 2h40s 192.168.4.238 18 22s601ms 1s255ms 192.168.4.27 6 70ms 11ms 192.168.4.33 91 17s967ms 197ms 192.168.4.35 1 165ms 165ms 192.168.4.98 330 14s219ms 43ms [local] 274 2m3s 452ms -
Checkpoints / Restartpoints
Checkpoints Buffers
Key values
- 12,152 buffers Checkpoint Peak
- 2025-03-31 05:08:03 Date
- 210.005 seconds Highest write time
- 0.012 seconds Sync time
Checkpoints Wal files
Key values
- 6 files Wal files usage Peak
- 2025-03-31 05:08:03 Date
Checkpoints distance
Key values
- 183.24 Mo Distance Peak
- 2025-03-31 05:08:03 Date
Checkpoints Activity
↑ Back to the top of the Checkpoint Activity tableDay Hour Written buffers Write time Sync time Total time Mar 31 05 39,246 1,573.201s 0.04s 1,573.518s Day Hour Added Removed Recycled Synced files Longest sync Average sync Mar 31 05 0 0 21 1,626 0.007s 0s Day Hour Count Avg time (sec) Mar 31 05 0 0s Day Hour Mean distance Mean estimate Mar 31 05 29,462.67 kB 68,400.08 kB -
Temporary Files
Size of temporary files
Key values
- 146.65 MiB Temp Files size Peak
- 2025-03-31 05:00:08 Date
Number of temporary files
Key values
- 30 per second Temp Files Peak
- 2025-03-31 05:32:10 Date
Temporary Files Activity
↑ Back to the top of the Temporary Files Activity tableDay Hour Count Total size Average size Mar 31 05 489 3.33 GiB 6.97 MiB Queries generating the most temporary files (N)
Rank Count Total size Min size Max size Avg size Query 1 144 620.71 MiB 3.21 MiB 9.30 MiB 4.31 MiB with rar_max as ( ;-
WITH rar_max as ( ;
Date: 2025-03-31 05:00:32 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver
2 38 1.53 GiB 7.33 MiB 130.76 MiB 41.13 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: 2025-03-31 05:30:09 Duration: 6s476ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown]
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with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-03-31 05:20:08 Duration: 5s807ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown]
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with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-03-31 05:00:08 Duration: 5s785ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown]
3 16 362.00 MiB 22.62 MiB 22.62 MiB 22.62 MiB update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type = ?) sub where result_uid = sub.resultuid;-
UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid;
Date: 2025-03-31 05:56:13 Duration: 1s159ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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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: 2025-03-31 05:11:12 Duration: 1s40ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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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: 2025-03-31 05:18:12 Duration: 1s27ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
4 16 624.12 MiB 39.01 MiB 39.01 MiB 39.01 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: 2025-03-31 05:16:15 Duration: 2s685ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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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: 2025-03-31 05:26:16 Duration: 2s671ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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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: 2025-03-31 05:01:15 Duration: 2s631ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
5 4 232.44 MiB 58.05 MiB 58.19 MiB 58.11 MiB select updateageforrelevantresults ();-
select updateageforrelevantresults ();
Date: 2025-03-31 05:17:13 Duration: 11s523ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-03-31 05:32:14 Duration: 11s452ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-03-31 05:02:13 Duration: 11s33ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
6 1 3.83 MiB 3.83 MiB 3.83 MiB 3.83 MiB select resultuid from relevance_consecutivecandles_results order by resultuid desc limit ?), all_results as ( select ccr.resultuid as resultuid, ccr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ccr.patternendtime as identified, dtt.timezone as timezone, ccr.qtyconsecutivecandles as length, g.basegroupname, case when rcr.age is not null then rcr.age when ccr.resultuid <= rm.resultuid then ? else ? end as age, case when rcr.relevant is not null then rcr.relevant when ccr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip, newlevels.filtered from consecutivecandles_results ccr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = ccr.symbolid inner join symbols s on ccr.symbolid = s.symbolid and s.nonliquid = ? inner join downloadersymbolsettings dss on ccr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on ccr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join rar_max rm on ? = ? left outer join relevance_consecutivecandles_results rcr on rcr.resultuid = ccr.resultuid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? left join lateral calc_cc_signal_filter (ccr.resultuid) newlevels on true where ccr.gmttimefound > now() - interval ? and s.deleted = ? and (ccr.simulation = ? or ccr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ccr.patternlengthbars <= ?)), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;-
SELECT resultuid FROM relevance_consecutivecandles_results ORDER BY resultuid DESC LIMIT 1), all_results AS ( SELECT ccr.resultuid AS resultuid, ccr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ccr.patternendtime AS identified, dtt.timezone AS timezone, ccr.qtyconsecutivecandles AS length, g.basegroupname, CASE WHEN rcr.age IS NOT NULL THEN rcr.age WHEN ccr.resultuid <= rm.resultuid THEN 1 ELSE 0 END as age, CASE WHEN rcr.relevant IS NOT NULL THEN rcr.relevant WHEN ccr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip, newLevels.filtered FROM consecutivecandles_results ccr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $1 AND bsl.symbolid = ccr.symbolid INNER JOIN symbols s ON ccr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON ccr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on ccr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_consecutivecandles_results rcr ON rcr.resultuid = ccr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' LEFT JOIN LATERAL calc_cc_signal_filter (ccr.resultuid) newLevels on true WHERE ccr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ($2 = 0 OR s.timegranularity in ($3, $4, $5, $6, $7, $8, $9)) AND ($10 = 0 OR s.exchange in ($11)) AND ($12 = 0 OR coalesce(bim.code, s.symbol) in ($13, $14, $15, $16, $17, $18, $19, $20, $21, $22, $23, $24, $25, $26, $27, $28, $29, $30, $31, $32, $33, $34, $35, $36, $37, $38, $39, $40, $41, $42, $43, $44, $45, $46, $47, $48, $49, $50, $51, $52, $53, $54, $55, $56, $57, $58, $59, $60, $61, $62, $63, $64, $65, $66, $67, $68, $69, $70, $71, $72, $73, $74, $75, $76, $77, $78, $79, $80, $81, $82, $83, $84, $85, $86, $87, $88, $89, $90, $91, $92, $93, $94, $95, $96, $97, $98, $99, $100, $101, $102, $103, $104, $105, $106, $107, $108, $109, $110, $111, $112, $113, $114, $115, $116, $117, $118, $119, $120, $121, $122, $123, $124, $125, $126, $127, $128, $129, $130, $131, $132, $133, $134, $135, $136, $137, $138, $139, $140, $141, $142, $143, $144, $145, $146, $147, $148, $149, $150, $151, $152, $153, $154, $155, $156, $157, $158, $159, $160, $161, $162, $163, $164, $165, $166, $167, $168, $169, $170, $171, $172, $173, $174, $175, $176, $177, $178, $179, $180, $181, $182, $183, $184, $185, $186, $187, $188, $189, $190, $191, $192, $193, $194, $195, $196, $197, $198, $199, $200, $201, $202, $203, $204, $205, $206, $207, $208, $209, $210, $211, $212, $213, $214, $215, $216, $217, $218, $219, $220, $221, $222, $223, $224, $225, $226, $227, $228, $229, $230, $231, $232, $233, $234, $235, $236, $237, $238, $239, $240, $241, $242, $243, $244, $245, $246, $247, $248, $249, $250, $251, $252, $253, $254, $255, $256, $257, $258, $259, $260, $261, $262, $263, $264, $265, $266, $267, $268, $269, $270, $271, $272, $273, $274, $275, $276, $277, $278, $279, $280, $281, $282, $283, $284, $285, $286, $287, $288, $289, $290, $291, $292, $293, $294, $295, $296, $297, $298, $299, $300, $301, $302, $303, $304, $305, $306, $307, $308, $309, $310, $311, $312, $313, $314, $315, $316, $317, $318, $319, $320, $321, $322)) AND ($323 = 0 OR ccr.patternlengthbars <= $324)), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = $325 OR relevant = 1) AND ($326 = 0 OR age <= $327) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-03-31 05:26:16 Duration: 0ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown]
Queries generating the largest temporary files
Rank Size Query 1 130.76 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 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: 2025-03-31 05:20:06 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.90 - Application: [unknown] ]
2 123.59 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: 2025-03-31 05:10:04 ]
3 94.23 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: 2025-03-31 05:30:05 ]
4 88.95 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: 2025-03-31 05:00:06 ]
5 86.41 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-03-31 05:40:04 ]
6 78.18 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: 2025-03-31 05:50:04 ]
7 77.11 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: 2025-03-31 05:40:04 ]
8 73.82 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: 2025-03-31 05:00:05 ]
9 71.74 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: 2025-03-31 05:50:04 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.90 - Application: [unknown] ]
10 68.20 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: 2025-03-31 05:30:08 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.90 - Application: [unknown] ]
11 58.19 MiB select updateageforrelevantresults ();[ Date: 2025-03-31 05:02:05 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
12 58.12 MiB select updateageforrelevantresults ();[ Date: 2025-03-31 05:32:06 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
13 58.07 MiB select updateageforrelevantresults ();[ Date: 2025-03-31 05:47:05 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
14 58.05 MiB select updateageforrelevantresults ();[ Date: 2025-03-31 05:17:05 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
15 52.87 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: 2025-03-31 05:10:07 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.90 - Application: [unknown] ]
16 49.09 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: 2025-03-31 05:40:05 ]
17 47.82 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: 2025-03-31 05:00:06 ]
18 44.73 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: 2025-03-31 05:50:04 ]
19 41.74 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: 2025-03-31 05:10:04 ]
20 39.38 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: 2025-03-31 05:20:05 ]
-
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)
- 59 analyzes Total
Table Number of analyzes acaweb_fx.public.solr_relevance_old 16 acaweb_fx.pg_catalog.pg_attribute 7 acaweb_fx.public.datafeeds_latestrun 4 acaweb_fx.public.relevance_keylevels_results 4 acaweb_fx.pg_catalog.pg_class 4 acaweb_fx.public.relevance_fibonacci_results 4 acaweb_fx.public.relevance_autochartist_results 4 acaweb_fx.public.latest_t15_candle_view 3 acaweb_fx.pg_catalog.pg_type 3 acaweb_fx.pg_catalog.pg_index 2 acaweb_fx.public.autochartist_symbolupdates 2 acaweb_fx.public.relevance_bigmovement_results 2 acaweb_fx.pg_catalog.pg_depend 1 acaweb_fx.public.latest_candle_datetime_per_receng 1 acaweb_fx.public.symbollatestupdatetime 1 acaweb_fx.public.correlating_signals 1 Total 59 Vacuums per table
Key values
- public.solr_relevance_old (16) Main table vacuumed on database acaweb_fx
- 39 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 13,543 0 51 0 0 10,116 16 1,883,060 acaweb_fx.public.datafeeds_latestrun 4 0 447 0 35 0 0 68 33 72,573 acaweb_fx.pg_toast.pg_toast_2619 2 2 284 0 48 0 0 221 47 210,613 acaweb_fx.pg_catalog.pg_attribute 2 2 1,594 0 344 0 128 765 280 1,705,090 acaweb_fx.public.relevance_keylevels_results 2 2 7,925 0 351 3 154 1,835 723 1,999,448 acaweb_fx.pg_catalog.pg_class 2 2 743 0 80 0 82 243 75 380,062 acaweb_fx.public.relevance_autochartist_results 2 2 7,036 0 191 2 492 1,417 176 486,351 acaweb_fx.public.relevance_fibonacci_results 2 2 2,492 0 38 1 112 340 21 97,627 acaweb_fx.pg_catalog.pg_index 1 1 104 0 16 0 0 28 15 91,836 acaweb_fx.pg_catalog.pg_type 1 1 154 0 20 0 0 53 22 111,257 acaweb_fx.public.autochartist_symbolupdates 1 1 22,826 0 3,434 6 38,225 6,362 3,390 1,168,520 acaweb_fx.pg_catalog.pg_statistic 1 1 827 0 153 0 686 466 139 600,401 acaweb_fx.public.relevance_bigmovement_results 1 1 199 0 11 0 0 72 10 41,196 acaweb_fx.public.latest_t15_candle_view 1 1 65 0 1 0 0 6 1 9,055 acaweb_fx.pg_catalog.pg_depend 1 1 344 0 86 0 58 192 74 419,543 Total 39 35 58,583 46,618 4,859 12 39,937 22,184 5,022 9,276,632 Tuples removed per table
Key values
- public.solr_relevance_old (83068) Main table with removed tuples on database acaweb_fx
- 97196 tuples Total removed
Index Tuples Pages Table Vacuums scans removed remain not yet removable removed remain acaweb_fx.public.solr_relevance_old 16 16 83,068 100,784 0 0 3,356 acaweb_fx.public.autochartist_symbolupdates 1 1 5,258 47,096 186 0 40,691 acaweb_fx.pg_catalog.pg_attribute 2 2 2,737 18,926 0 0 484 acaweb_fx.public.relevance_keylevels_results 2 2 1,915 23,631 0 0 558 acaweb_fx.public.relevance_autochartist_results 2 2 1,446 16,592 0 0 760 acaweb_fx.pg_catalog.pg_statistic 1 1 673 4,422 0 0 1,194 acaweb_fx.pg_catalog.pg_depend 1 1 631 12,029 0 0 114 acaweb_fx.pg_catalog.pg_class 2 2 316 3,894 0 0 300 acaweb_fx.public.relevance_fibonacci_results 2 2 291 2,815 0 0 204 acaweb_fx.public.datafeeds_latestrun 4 0 250 77 17 0 64 acaweb_fx.public.relevance_bigmovement_results 1 1 239 1,292 0 0 31 acaweb_fx.pg_catalog.pg_type 1 1 149 1,338 0 0 38 acaweb_fx.pg_toast.pg_toast_2619 2 2 142 347 8 0 102 acaweb_fx.public.latest_t15_candle_view 1 1 63 14 0 0 1 acaweb_fx.pg_catalog.pg_index 1 1 18 813 0 0 22 Total 39 35 97,196 234,070 211 0 47,919 Pages removed per table
Key values
- unknown (0) Main table with removed pages on database unknown
- 0 pages Total removed
Pages removed per tables
NO DATASET
Table Number of vacuums Index scans Tuples removed Pages removed acaweb_fx.pg_catalog.pg_index 1 1 18 0 acaweb_fx.pg_toast.pg_toast_2619 2 2 142 0 acaweb_fx.pg_catalog.pg_type 1 1 149 0 acaweb_fx.public.autochartist_symbolupdates 1 1 5258 0 acaweb_fx.public.datafeeds_latestrun 4 0 250 0 acaweb_fx.pg_catalog.pg_statistic 1 1 673 0 acaweb_fx.pg_catalog.pg_attribute 2 2 2737 0 acaweb_fx.public.relevance_bigmovement_results 1 1 239 0 acaweb_fx.public.latest_t15_candle_view 1 1 63 0 acaweb_fx.pg_catalog.pg_depend 1 1 631 0 acaweb_fx.public.relevance_keylevels_results 2 2 1915 0 acaweb_fx.pg_catalog.pg_class 2 2 316 0 acaweb_fx.public.solr_relevance_old 16 16 83068 0 acaweb_fx.public.relevance_autochartist_results 2 2 1446 0 acaweb_fx.public.relevance_fibonacci_results 2 2 291 0 Total 39 35 97,196 0 Autovacuum Activity
↑ Back to the top of the Autovacuum Activity tableDay Hour VACUUMs ANALYZEs Mar 31 05 39 59 - 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
- 69,234 Total read queries
- 37,220 Total write queries
Queries by database
Key values
- acaweb_fx Main database
- 108,326 Requests
- 2h1m20s (acaweb_fx)
- Main time consuming database
Database Request type Count Duration acaweb_fx Total 108,326 2h1m20s copy from 96 7s136ms copy to 26 18s967ms cte 3,102 1h56m59s ddl 16 540ms delete 16 26ms insert 25,503 18s728ms others 2,543 9s705ms select 68,919 3m6s tcl 5,722 2s958ms update 2,383 17s383ms socialmedia Total 671 738ms insert 292 387ms select 315 240ms update 64 110ms Queries by user
Key values
- postgres Main user
- 108,997 Requests
User Request type Count Duration postgres Total 108,997 2h1m21s copy from 96 7s136ms copy to 26 18s967ms cte 3,102 1h56m59s ddl 16 540ms delete 16 26ms insert 25,795 19s116ms others 2,543 9s705ms select 69,234 3m6s tcl 5,722 2s958ms update 2,447 17s493ms Duration by user
Key values
- 2h1m21s (postgres) Main time consuming user
User Request type Count Duration postgres Total 108,997 2h1m21s copy from 96 7s136ms copy to 26 18s967ms cte 3,102 1h56m59s ddl 16 540ms delete 16 26ms insert 25,795 19s116ms others 2,543 9s705ms select 69,234 3m6s tcl 5,722 2s958ms update 2,447 17s493ms Queries by host
Key values
- 192.168.1.20 Main host
- 27,844 Requests
- 41m39s (192.168.1.250)
- Main time consuming host
Host Request type Count Duration 127.0.0.1 Total 24,279 59s306ms copy to 26 18s967ms cte 24 294ms insert 13,523 8s789ms others 38 0ms select 3,770 27s485ms tcl 5,046 2s755ms update 1,852 1s13ms 182.165.1.42 Total 194 8m37s cte 66 8m36s others 4 0ms select 124 130ms 192.168.0.114 Total 32 31ms select 10 12ms tcl 16 7ms update 6 11ms 192.168.0.216 Total 400 356ms others 200 19ms select 192 219ms update 8 117ms 192.168.0.236 Total 12 1ms cte 2 0ms select 10 1ms 192.168.0.239 Total 322 274ms select 322 274ms 192.168.0.42 Total 583 673ms insert 34 2ms select 549 670ms 192.168.1.135 Total 116 265ms cte 8 152ms select 108 112ms 192.168.1.145 Total 26,595 33m5s cte 773 32m37s others 270 3ms select 25,552 27s532ms 192.168.1.20 Total 27,844 33m4s cte 770 32m37s others 314 3ms select 26,760 26s855ms 192.168.1.201 Total 1,548 1s826ms select 1,548 1s826ms 192.168.1.23 Total 4,995 30s517ms others 1,112 13ms select 3,883 30s504ms 192.168.1.239 Total 48 28ms others 24 2ms select 24 26ms 192.168.1.250 Total 5,871 41m39s cte 1,338 41m37s others 206 2ms select 4,327 1s950ms 192.168.1.90 Total 60 32s740ms cte 6 32s697ms others 8 0ms select 46 42ms 192.168.1.97 Total 12 1ms cte 2 0ms select 10 1ms 192.168.2.126 Total 80 66ms others 18 0ms select 62 66ms 192.168.2.182 Total 48 247ms others 24 2ms select 12 11ms update 12 233ms 192.168.2.205 Total 138 102ms insert 90 9ms others 24 2ms select 20 19ms update 4 70ms 192.168.2.82 Total 766 1s448ms insert 410 688ms others 94 10ms select 159 97ms update 103 652ms 192.168.3.199 Total 252 277ms others 126 12ms select 114 120ms update 12 144ms 192.168.4.142 Total 12,700 10s395ms insert 11,444 9s231ms select 1,256 1s163ms 192.168.4.150 Total 22 997ms others 21 0ms select 1 997ms 192.168.4.238 Total 54 21s563ms cte 16 21s556ms insert 2 7ms others 36 0ms 192.168.4.27 Total 18 1ms others 12 0ms select 4 1ms update 2 0ms 192.168.4.33 Total 671 738ms insert 292 387ms select 315 240ms update 64 110ms 192.168.4.35 Total 3 48ms cte 1 48ms others 2 0ms 192.168.4.98 Total 996 10s140ms others 6 9s349ms select 6 29ms tcl 660 195ms update 324 566ms [local] Total 338 2m3s copy from 96 7s136ms cte 96 34s753ms ddl 16 540ms delete 16 26ms others 4 283ms select 50 1m5s update 60 14s573ms Queries by application
Key values
- PostgreSQL JDBC Driver Main application
- 67,033 Requests
- 1h48m45s (PostgreSQL JDBC Driver)
- Main time consuming application
Application Request type Count Duration PostgreSQL JDBC Driver Total 67,033 1h48m45s cte 2,906 1h47m14s insert 36 9ms others 999 14ms select 63,090 1m30s update 2 0ms [unknown] Total 41,516 10m13s cte 76 9m9s insert 25,759 19s106ms others 1,540 9s407ms select 6,042 29s461ms tcl 5,722 2s958ms update 2,377 2s902ms psql Total 448 2m22s copy from 96 7s136ms copy to 26 18s967ms cte 120 35s47ms ddl 16 540ms delete 16 26ms others 4 283ms select 102 1m6s update 68 14s590ms Number of cancelled queries
Key values
- 0 per second Cancelled query Peak
- 2025-03-31 05:27:07 Date
Number of cancelled queries (5 minutes period)
NO DATASET
-
Top Queries
Histogram of query times
Key values
- 71,898 0-1ms duration
Slowest individual queries
Rank Duration Query 1 38s424ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), 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 = 't' 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 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 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 = 3 INNER JOIN rar_max rm ON 1 = 1 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 = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-03-31 05:56:12 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
2 36s195ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), 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 = 't' 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 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 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 = 3 INNER JOIN rar_max rm ON 1 = 1 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 = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-03-31 05:50:50 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
3 35s480ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), 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 = 't' 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 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 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 = 3 INNER JOIN rar_max rm ON 1 = 1 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 = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-03-31 05:18:32 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
4 35s471ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), 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 = 't' 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 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 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 = 3 INNER JOIN rar_max rm ON 1 = 1 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 = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-03-31 05:22:05 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
5 35s332ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), 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 = 't' 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 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 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 = 3 INNER JOIN rar_max rm ON 1 = 1 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 = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-03-31 05:27:24 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
6 34s781ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), 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 = 't' 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 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 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 = 3 INNER JOIN rar_max rm ON 1 = 1 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 = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-03-31 05:43:21 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
7 34s521ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), 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 = 't' 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 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 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 = 3 INNER JOIN rar_max rm ON 1 = 1 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 = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-03-31 05:34:15 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
8 24s491ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), 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 = 't' 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 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 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 = 3 INNER JOIN rar_max rm ON 1 = 1 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 = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR p.patternname in ('')) AND ('2' = 0 OR kr.patternclassid in ('1', '2')) AND ('400' = 0 OR kr.patternlengthbars <= '400') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-03-31 05:46:18 - Database: acaweb_fx - User: postgres - Remote: 182.165.1.42 - Application: [unknown] - Bind query: yes ]
9 24s93ms WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;[ Date: 2025-03-31 05:20:54 - Database: acaweb_fx - User: postgres - Remote: 182.165.1.42 - Application: [unknown] - Bind query: yes ]
10 22s984ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), 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 = 't' 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 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 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 = 3 INNER JOIN rar_max rm ON 1 = 1 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 = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR p.patternname in ('')) AND ('2' = 0 OR kr.patternclassid in ('1', '2')) AND ('400' = 0 OR kr.patternlengthbars <= '400') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-03-31 05:26:16 - Database: acaweb_fx - User: postgres - Remote: 182.165.1.42 - Application: [unknown] - Bind query: yes ]
11 22s595ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), 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 = 't' 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 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 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 = 3 INNER JOIN rar_max rm ON 1 = 1 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 = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR p.patternname in ('')) AND ('2' = 0 OR kr.patternclassid in ('1', '2')) AND ('400' = 0 OR kr.patternlengthbars <= '400') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-03-31 05:16:17 - Database: acaweb_fx - User: postgres - Remote: 182.165.1.42 - Application: [unknown] - Bind query: yes ]
12 20s820ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), 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 = 't' 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 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 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 = 3 INNER JOIN rar_max rm ON 1 = 1 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 = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR p.patternname in ('')) AND ('2' = 0 OR kr.patternclassid in ('1', '2')) AND ('400' = 0 OR kr.patternlengthbars <= '400') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-03-31 05:51:14 - Database: acaweb_fx - User: postgres - Remote: 182.165.1.42 - Application: [unknown] - Bind query: yes ]
13 20s438ms WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;[ Date: 2025-03-31 05:00:50 - Database: acaweb_fx - User: postgres - Remote: 182.165.1.42 - Application: [unknown] - Bind query: yes ]
14 19s183ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), 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 = 't' 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 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 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 = 3 INNER JOIN rar_max rm ON 1 = 1 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 = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR p.patternname in ('')) AND ('2' = 0 OR kr.patternclassid in ('1', '2')) AND ('400' = 0 OR kr.patternlengthbars <= '400') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-03-31 05:56:15 - Database: acaweb_fx - User: postgres - Remote: 182.165.1.42 - Application: [unknown] - Bind query: yes ]
15 18s465ms WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;[ Date: 2025-03-31 05:17:07 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.145 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
16 18s131ms WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;[ Date: 2025-03-31 05:52:10 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.20 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
17 18s32ms WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('0' = 0 OR ar.patternlengthbars <= '0') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;[ Date: 2025-03-31 05:51:18 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
18 17s660ms WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('0' = 0 OR ar.patternlengthbars <= '0') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;[ Date: 2025-03-31 05:21:24 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
19 17s612ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), 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 = 't' 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 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 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 = 3 INNER JOIN rar_max rm ON 1 = 1 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 = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR p.patternname in ('')) AND ('2' = 0 OR kr.patternclassid in ('1', '2')) AND ('400' = 0 OR kr.patternlengthbars <= '400') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-03-31 05:01:15 - Database: acaweb_fx - User: postgres - Remote: 182.165.1.42 - Application: [unknown] - Bind query: yes ]
20 17s520ms WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;[ Date: 2025-03-31 05:52:09 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.145 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
Time consuming queries
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 49m39s 346 407ms 24s93ms 8s610ms with rar_max as ( select resultuid from relevance_autochartist_results order by resultuid desc limit ? ), ar as ( select a.*, rr.age, rr.relevant from autochartist_results a left outer join relevance_autochartist_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_autochartist_results) end ), all_results as ( select ar.resultuid as resultuid, ar.direction as direction, ar.predictiontimeto as predictiontimeto, ar.predictionpricefrom as predictionpricefrom, ar.predictionpriceto as predictionpriceto, cp.pip as pip, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ar.pattern as pattern_name, ar.breakout as breakout, ar.patternendtime as identified, dtt.timezone as timezone, ar.patternlengthbars as length, g.basegroupname, newlevels.profit, newlevels.stop, newlevels.filtered, case when ar.age is not null then ar.age when ar.resultuid <= rm.resultuid then ? else ? end as age, case when ar.relevant is not null then ar.relevant when ar.resultuid <= rm.resultuid then ? else ? end as relevant from ar inner join symbols s on ar.symbolid = s.symbolid and s.nonliquid = ? inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = s.symbolid inner join symbolgroup sg on bsl.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join downloadersymbolsettings dss on sg.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left outer join autochartist_symbolupdates au on dss.symbolid = au.symbolid left outer join currencypips cp on s.symbol = cp.symbol left join lateral calc_cp_signal (ar.resultuid) newlevels on true left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where ar.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (ar.simulation = ? or ar.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ar.pattern in (...)) and (? = ? or (? = ? and ar.breakout >= ?) or (? = ? and ar.breakout < ?)) and (? = ? or ar.patternlengthbars <= ?) and newlevels.filtered = false and ar.patternstarttime >= coalesce(au.earliestpricedatetime, ?::timestamp without time zone) -- to make sure patternstarttime is in our t-tables ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Mar 31 05 346 49m39s 8s610ms [ User: postgres - Total duration: 49m39s - Times executed: 346 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 46m9s - Times executed: 334 ]
[ Application: [unknown] - Total duration: 3m29s - Times executed: 12 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-03-31 05:20:54 Duration: 24s93ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-03-31 05:00:50 Duration: 20s438ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-03-31 05:17:07 Duration: 18s465ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
2 47m48s 345 172ms 38s424ms 8s315ms 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 #2
Day Hour Count Duration Avg duration Mar 31 05 345 47m48s 8s315ms [ User: postgres - Total duration: 47m48s - Times executed: 345 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 44m7s - Times executed: 333 ]
[ Application: [unknown] - Total duration: 3m41s - Times executed: 12 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), 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 = 't' 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 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 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 = 3 INNER JOIN rar_max rm ON 1 = 1 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 = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-03-31 05:56:12 Duration: 38s424ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), 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 = 't' 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 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 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 = 3 INNER JOIN rar_max rm ON 1 = 1 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 = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-03-31 05:50:50 Duration: 36s195ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), 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 = 't' 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 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 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 = 3 INNER JOIN rar_max rm ON 1 = 1 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 = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-03-31 05:18:32 Duration: 35s480ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
3 14m36s 313 638ms 8s137ms 2s800ms with rar_max as ( select resultuid from relevance_fibonacci_results order by resultuid desc limit ? ), fr as ( select a.*, rr.age, rr.relevant from fibonacci_results a left outer join relevance_fibonacci_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) end ), all_results as ( select fr.resultuid as resultuid, fr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, fr.pattern as pattern_name, fr.timed as timed, fr.patternendtime as identified, dtt.timezone as timezone, fr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when fr.age is not null then fr.age when fr.resultuid <= rm.resultuid then ? else ? end as age, case when fr.relevant is not null then fr.relevant when fr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from fr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = fr.symbolid inner join symbols s on fr.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on fr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join downloadersymbolsettings dss on fr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left join lateral calc_fib_signal_filter (fr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where fr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (fr.simulation = ? or fr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or fr.pattern in (...)) and (? = ? or fr.patternlengthbars <= ?) and (? = ? or (? = ? and fr.timed > cast(? as timestamp)) or (? = ? and fr.timed < cast(? as timestamp))) ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Mar 31 05 313 14m36s 2s800ms [ User: postgres - Total duration: 14m36s - Times executed: 313 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 13m31s - Times executed: 301 ]
[ Application: [unknown] - Total duration: 1m4s - Times executed: 12 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1 ), fr AS ( SELECT a.*, rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END ), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR fr.pattern in ('')) AND ('0' = 0 OR fr.patternlengthbars <= '0') AND ('0' = 0 OR ('0' = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ('0' = 2 AND fr.timed < cast('1970-01-01' as timestamp))) ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-03-31 05:17:11 Duration: 8s137ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1 ), fr AS ( SELECT a.*, rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END ), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR fr.pattern in ('')) AND ('400' = 0 OR fr.patternlengthbars <= '400') AND ('0' = 0 OR ('0' = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ('0' = 2 AND fr.timed < cast('1970-01-01' as timestamp))) ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-03-31 05:55:55 Duration: 8s131ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1 ), fr AS ( SELECT a.*, rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END ), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('0' = 0 OR fr.pattern in ('')) AND ('400' = 0 OR fr.patternlengthbars <= '400') AND ('0' = 0 OR ('0' = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ('0' = 2 AND fr.timed < cast('1970-01-01' as timestamp))) ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-03-31 05:17:14 Duration: 7s431ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
4 2m9s 231 147ms 1s678ms 560ms with rar_max as ( select resultuid from relevance_consecutivecandles_results order by resultuid desc limit ? ), all_results as ( select ccr.resultuid as resultuid, ccr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ccr.patternendtime as identified, dtt.timezone as timezone, ccr.qtyconsecutivecandles as length, g.basegroupname, case when rcr.age is not null then rcr.age when ccr.resultuid <= rm.resultuid then ? else ? end as age, case when rcr.relevant is not null then rcr.relevant when ccr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip, newlevels.filtered from consecutivecandles_results ccr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = ccr.symbolid inner join symbols s on ccr.symbolid = s.symbolid and s.nonliquid = ? inner join downloadersymbolsettings dss on ccr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on ccr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join rar_max rm on ? = ? left outer join relevance_consecutivecandles_results rcr on rcr.resultuid = ccr.resultuid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? left join lateral calc_cc_signal_filter (ccr.resultuid) newlevels on true where ccr.gmttimefound > now() - interval ? and s.deleted = ? and (ccr.simulation = ? or ccr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ccr.patternlengthbars <= ?) ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Mar 31 05 231 2m9s 560ms [ User: postgres - Total duration: 2m9s - Times executed: 231 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m52s - Times executed: 219 ]
[ Application: [unknown] - Total duration: 17s31ms - Times executed: 12 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_consecutivecandles_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT ccr.resultuid AS resultuid, ccr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ccr.patternendtime AS identified, dtt.timezone AS timezone, ccr.qtyconsecutivecandles AS length, g.basegroupname, CASE WHEN rcr.age IS NOT NULL THEN rcr.age WHEN ccr.resultuid <= rm.resultuid THEN 1 ELSE 0 END as age, CASE WHEN rcr.relevant IS NOT NULL THEN rcr.relevant WHEN ccr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip, newLevels.filtered FROM consecutivecandles_results ccr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = ccr.symbolid INNER JOIN symbols s ON ccr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON ccr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on ccr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_consecutivecandles_results rcr ON rcr.resultuid = ccr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' LEFT JOIN LATERAL calc_cc_signal_filter (ccr.resultuid) newLevels on true WHERE ccr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('400' = 0 OR ccr.patternlengthbars <= '400') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-03-31 05:26:18 Duration: 1s678ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_consecutivecandles_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT ccr.resultuid AS resultuid, ccr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ccr.patternendtime AS identified, dtt.timezone AS timezone, ccr.qtyconsecutivecandles AS length, g.basegroupname, CASE WHEN rcr.age IS NOT NULL THEN rcr.age WHEN ccr.resultuid <= rm.resultuid THEN 1 ELSE 0 END as age, CASE WHEN rcr.relevant IS NOT NULL THEN rcr.relevant WHEN ccr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip, newLevels.filtered FROM consecutivecandles_results ccr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = ccr.symbolid INNER JOIN symbols s ON ccr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON ccr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on ccr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_consecutivecandles_results rcr ON rcr.resultuid = ccr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' LEFT JOIN LATERAL calc_cc_signal_filter (ccr.resultuid) newLevels on true WHERE ccr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('400' = 0 OR ccr.patternlengthbars <= '400') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-03-31 05:56:17 Duration: 1s633ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_consecutivecandles_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT ccr.resultuid AS resultuid, ccr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ccr.patternendtime AS identified, dtt.timezone AS timezone, ccr.qtyconsecutivecandles AS length, g.basegroupname, CASE WHEN rcr.age IS NOT NULL THEN rcr.age WHEN ccr.resultuid <= rm.resultuid THEN 1 ELSE 0 END as age, CASE WHEN rcr.relevant IS NOT NULL THEN rcr.relevant WHEN ccr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip, newLevels.filtered FROM consecutivecandles_results ccr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = ccr.symbolid INNER JOIN symbols s ON ccr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON ccr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on ccr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_consecutivecandles_results rcr ON rcr.resultuid = ccr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' LEFT JOIN LATERAL calc_cc_signal_filter (ccr.resultuid) newLevels on true WHERE ccr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('400' = 0 OR ccr.patternlengthbars <= '400') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-03-31 05:16:19 Duration: 1s628ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
5 47s750ms 135 85ms 904ms 353ms with last_candle as ( select acs.symbolid as symbolid, acs.latestpricedatetime as latest_candle_time, bsl.brokerid as broker_id, coalesce(bim.code, s.symbol) as symbol, bim.code as symbol_mapping, s.exchange as exchange, s.timegranularity as timegranularity from autochartist_symbolupdates acs inner join brokersymbollist bsl on acs.symbolid = bsl.symbolid inner join symbols s on acs.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where bsl.brokerid = ? and s.deleted = ? and s.nonliquid = ? and acs.latestpricedatetime is not null ) select * from ( select lc.broker_id as brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / ?) + ? as sast_hh, mod(cast(psp.fromtime as int), ?) as sast_mm, current_timestamp as datetime, (powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice as closingprice, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / ?.?) as low_15, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / ?.?) as high_15, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / ?.?) as low_30, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / ?.?) as high_30, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / ?.?) as low_60, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / ?.?) as high_60, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / ?.?) as low_240, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / ?.?) as high_240, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / ?.?) as low_1440, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / ?.?) as high_1440, dtt.absolutetimezoneoffset as datafeedtimezoneoffset, dtt.timezone as datafeedtimezonename, (round((cast(? as float) - rank) / ? * ?)) as rank_rounded, ((cast(? as float) - rank) / ? * ?) as rank from last_candle lc inner join downloadersymbolsettings dss on lc.symbolid = dss.symbolid inner join datafeedstimetable dtt on trim(dss.classname) = trim(dtt.classname) and dtt.dayofweek = ? -- assuming timezone is same for whole week. inner join powerstats_symboldata psd on psd.symbolid = lc.symbolid left outer join powerstats_trumpet psp on psd.trumpetsymbolid = psp.symbolid and psp.dayofweek = extract(dow from lc.latest_candle_time) and psp.fromtime = cast(extract(? from lc.latest_candle_time) as integer) * ? + extract(? from (cast(extract(? from lc.latest_candle_time) as integer) / ?) * ? * interval ?) inner join prfsymboltree prf on psd.symbolid = prf.symbolid and date_trunc(?, prf.enddate) = date_trunc(?, psp.enddate) left join lateral ( select ph.hour, (ave + stddev) as volatility, rank() over (order by (ave + stddev) desc) as rank from powerstats_hourly ph where ph.symbolid = psd.hourlysymbolid and date_trunc(?,ph.enddate) = date_trunc(?, prf.enddate) ) rank_query on true where prf.brokerid = ? and rank_query.hour = floor((psp.fromtime) / ?) and volatility > ? order by rank desc, rank_rounded desc, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Mar 31 05 135 47s750ms 353ms [ User: postgres - Total duration: 47s750ms - Times executed: 135 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 47s750ms - Times executed: 135 ]
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WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '529' AND s.deleted = 0 AND s.nonliquid = 0 AND acs.latestpricedatetime IS NOT NULL ) SELECT * FROM ( SELECT lc.broker_id AS brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / 60) + 6 as SAST_HH, mod(cast(psp.fromtime as int), 60) as SAST_MM, current_timestamp AS datetime, (PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice AS closingprice, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / 2.0) AS low_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / 2.0) AS high_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / 2.0) AS low_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / 2.0) AS high_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / 2.0) AS low_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / 2.0) AS high_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / 2.0) AS low_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / 2.0) AS high_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / 2.0) AS low_1440, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / 2.0) AS high_1440, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, (round((cast(25 as float) - rank) / 24 * 10)) as rank_rounded, ((cast(25 as float) - rank) / 24 * 10) as rank FROM last_candle lc INNER JOIN downloadersymbolsettings dss ON lc.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON TRIM(dss.classname) = TRIM(dtt.classname) and dtt.dayofweek = 3 -- assuming timezone is same for whole week. INNER JOIN powerstats_symboldata psd ON psd.symbolid = lc.symbolid LEFT OUTER JOIN powerstats_trumpet psp ON psd.trumpetsymbolid = psp.symbolid AND psp.dayofweek = extract(dow from lc.latest_candle_time) AND psp.fromtime = cast(extract('hour' from lc.latest_candle_time) as integer) * 60 + extract('minute' from (cast(extract('minute' from lc.latest_candle_time) as integer) / 15) * 15 * interval '1 minutes') INNER JOIN prfsymboltree prf ON psd.symbolid = prf.symbolid and DATE_TRUNC('day', prf.enddate) = DATE_TRUNC('day', psp.enddate) LEFT JOIN LATERAL ( SELECT ph.hour, (ave + stddev) AS volatility, rank() over (ORDER BY (ave + stddev) DESC) AS rank FROM powerstats_hourly ph WHERE ph.symbolid = psd.hourlysymbolid AND DATE_TRUNC('day', ph.enddate) = DATE_TRUNC('day', prf.enddate)) rank_query ON true WHERE prf.brokerid = '529' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2025-03-31 05:16:00 Duration: 904ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '529' AND s.deleted = 0 AND s.nonliquid = 0 AND acs.latestpricedatetime IS NOT NULL ) SELECT * FROM ( SELECT lc.broker_id AS brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / 60) + 6 as SAST_HH, mod(cast(psp.fromtime as int), 60) as SAST_MM, current_timestamp AS datetime, (PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice AS closingprice, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / 2.0) AS low_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / 2.0) AS high_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / 2.0) AS low_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / 2.0) AS high_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / 2.0) AS low_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / 2.0) AS high_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / 2.0) AS low_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / 2.0) AS high_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / 2.0) AS low_1440, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / 2.0) AS high_1440, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, (round((cast(25 as float) - rank) / 24 * 10)) as rank_rounded, ((cast(25 as float) - rank) / 24 * 10) as rank FROM last_candle lc INNER JOIN downloadersymbolsettings dss ON lc.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON TRIM(dss.classname) = TRIM(dtt.classname) and dtt.dayofweek = 3 -- assuming timezone is same for whole week. INNER JOIN powerstats_symboldata psd ON psd.symbolid = lc.symbolid LEFT OUTER JOIN powerstats_trumpet psp ON psd.trumpetsymbolid = psp.symbolid AND psp.dayofweek = extract(dow from lc.latest_candle_time) AND psp.fromtime = cast(extract('hour' from lc.latest_candle_time) as integer) * 60 + extract('minute' from (cast(extract('minute' from lc.latest_candle_time) as integer) / 15) * 15 * interval '1 minutes') INNER JOIN prfsymboltree prf ON psd.symbolid = prf.symbolid and DATE_TRUNC('day', prf.enddate) = DATE_TRUNC('day', psp.enddate) LEFT JOIN LATERAL ( SELECT ph.hour, (ave + stddev) AS volatility, rank() over (ORDER BY (ave + stddev) DESC) AS rank FROM powerstats_hourly ph WHERE ph.symbolid = psd.hourlysymbolid AND DATE_TRUNC('day', ph.enddate) = DATE_TRUNC('day', prf.enddate)) rank_query ON true WHERE prf.brokerid = '529' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2025-03-31 05:16:00 Duration: 877ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '529' AND s.deleted = 0 AND s.nonliquid = 0 AND acs.latestpricedatetime IS NOT NULL ) SELECT * FROM ( SELECT lc.broker_id AS brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / 60) + 6 as SAST_HH, mod(cast(psp.fromtime as int), 60) as SAST_MM, current_timestamp AS datetime, (PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice AS closingprice, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / 2.0) AS low_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / 2.0) AS high_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / 2.0) AS low_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / 2.0) AS high_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / 2.0) AS low_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / 2.0) AS high_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / 2.0) AS low_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / 2.0) AS high_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / 2.0) AS low_1440, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / 2.0) AS high_1440, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, (round((cast(25 as float) - rank) / 24 * 10)) as rank_rounded, ((cast(25 as float) - rank) / 24 * 10) as rank FROM last_candle lc INNER JOIN downloadersymbolsettings dss ON lc.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON TRIM(dss.classname) = TRIM(dtt.classname) and dtt.dayofweek = 3 -- assuming timezone is same for whole week. INNER JOIN powerstats_symboldata psd ON psd.symbolid = lc.symbolid LEFT OUTER JOIN powerstats_trumpet psp ON psd.trumpetsymbolid = psp.symbolid AND psp.dayofweek = extract(dow from lc.latest_candle_time) AND psp.fromtime = cast(extract('hour' from lc.latest_candle_time) as integer) * 60 + extract('minute' from (cast(extract('minute' from lc.latest_candle_time) as integer) / 15) * 15 * interval '1 minutes') INNER JOIN prfsymboltree prf ON psd.symbolid = prf.symbolid and DATE_TRUNC('day', prf.enddate) = DATE_TRUNC('day', psp.enddate) LEFT JOIN LATERAL ( SELECT ph.hour, (ave + stddev) AS volatility, rank() over (ORDER BY (ave + stddev) DESC) AS rank FROM powerstats_hourly ph WHERE ph.symbolid = psd.hourlysymbolid AND DATE_TRUNC('day', ph.enddate) = DATE_TRUNC('day', prf.enddate)) rank_query ON true WHERE prf.brokerid = '529' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2025-03-31 05:28:00 Duration: 846ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
6 45s32ms 4 11s22ms 11s523ms 11s258ms select updateageforrelevantresults ();Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Mar 31 05 4 45s32ms 11s258ms [ User: postgres - Total duration: 45s32ms - Times executed: 4 ]
[ Application: psql - Total duration: 45s32ms - Times executed: 4 ]
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select updateageforrelevantresults ();
Date: 2025-03-31 05:17:13 Duration: 11s523ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-03-31 05:32:14 Duration: 11s452ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-03-31 05:02:13 Duration: 11s33ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
7 33s946ms 15,112 0ms 22ms 2ms 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 #7
Day Hour Count Duration Avg duration Mar 31 05 15,112 33s946ms 2ms [ User: postgres - Total duration: 33s946ms - Times executed: 15112 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 33s946ms - Times executed: 15112 ]
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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 = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '558' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'EURAUD' OR dss.downloadersymbol = 'EURAUD') AND dss.enabled = 1;
Date: 2025-03-31 05:00:04 Duration: 22ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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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 = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '558' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'AUDCAD' OR dss.downloadersymbol = 'AUDCAD') AND dss.enabled = 1;
Date: 2025-03-31 05:00:03 Duration: 20ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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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 = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'NZDCHF' OR dss.downloadersymbol = 'NZDCHF') AND dss.enabled = 1;
Date: 2025-03-31 05:30:06 Duration: 19ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
8 32s697ms 6 4s669ms 6s476ms 5s449ms 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 = ?;Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Mar 31 05 6 32s697ms 5s449ms [ User: postgres - Total duration: 32s697ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 32s697ms - Times executed: 6 ]
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with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-03-31 05:30:09 Duration: 6s476ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
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with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-03-31 05:20:08 Duration: 5s807ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
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with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-03-31 05:00:08 Duration: 5s785ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
9 32s113ms 16 1s594ms 2s685ms 2s7ms 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;Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Mar 31 05 16 32s113ms 2s7ms [ User: postgres - Total duration: 32s113ms - Times executed: 16 ]
[ Application: psql - Total duration: 32s113ms - Times executed: 16 ]
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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: 2025-03-31 05:16:15 Duration: 2s685ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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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: 2025-03-31 05:26:16 Duration: 2s671ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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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: 2025-03-31 05:01:15 Duration: 2s631ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
10 25s299ms 231 25ms 435ms 109ms with rar_max as ( select resultuid from relevance_bigmovement_results order by resultuid desc limit ? ), all_results as ( select bmr.resultuid as resultuid, ? 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, bmr.patternendtime as identified, bmr.patternlengthbars, dtt.timezone as timezone, g.basegroupname, 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 brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = bmr.symbolid inner join symbols s on bmr.symbolid = s.symbolid and s.nonliquid = ? inner join downloadersymbolsettings dss on bmr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on bmr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join rar_max rm on ? = ? left outer join relevance_bigmovement_results rbr on rbr.resultuid = bmr.resultuid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where bmr.gmttimefound > now() - interval ? and s.deleted = ? and (bmr.simulation = ? or bmr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or bmr.patternlengthbars <= ?) ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, interval desc;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Mar 31 05 231 25s299ms 109ms [ User: postgres - Total duration: 25s299ms - Times executed: 231 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 21s133ms - Times executed: 219 ]
[ Application: [unknown] - Total duration: 4s165ms - Times executed: 12 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_bigmovement_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT bmr.resultuid AS resultuid, 0 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, bmr.patternendtime AS identified, bmr.patternlengthbars, dtt.timezone AS timezone, g.basegroupname, CASE WHEN rbr.age IS NOT NULL THEN rbr.age WHEN bmr.resultuid <= rm.resultuid THEN 4 ELSE 0 END as age, CASE WHEN rbr.relevant IS NOT NULL THEN rbr.relevant WHEN bmr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM bigmovement_results bmr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = bmr.symbolid INNER JOIN symbols s ON bmr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON bmr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on bmr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_bigmovement_results rbr ON rbr.resultuid = bmr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bmr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (bmr.simulation = 0 OR bmr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('400' = 0 OR bmr.patternlengthbars <= '400') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, interval DESC;
Date: 2025-03-31 05:31:14 Duration: 435ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_bigmovement_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT bmr.resultuid AS resultuid, 0 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, bmr.patternendtime AS identified, bmr.patternlengthbars, dtt.timezone AS timezone, g.basegroupname, CASE WHEN rbr.age IS NOT NULL THEN rbr.age WHEN bmr.resultuid <= rm.resultuid THEN 4 ELSE 0 END as age, CASE WHEN rbr.relevant IS NOT NULL THEN rbr.relevant WHEN bmr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM bigmovement_results bmr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = bmr.symbolid INNER JOIN symbols s ON bmr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON bmr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on bmr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_bigmovement_results rbr ON rbr.resultuid = bmr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bmr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (bmr.simulation = 0 OR bmr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('400' = 0 OR bmr.patternlengthbars <= '400') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, interval DESC;
Date: 2025-03-31 05:16:20 Duration: 419ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_bigmovement_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT bmr.resultuid AS resultuid, 0 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, bmr.patternendtime AS identified, bmr.patternlengthbars, dtt.timezone AS timezone, g.basegroupname, CASE WHEN rbr.age IS NOT NULL THEN rbr.age WHEN bmr.resultuid <= rm.resultuid THEN 4 ELSE 0 END as age, CASE WHEN rbr.relevant IS NOT NULL THEN rbr.relevant WHEN bmr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM bigmovement_results bmr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = bmr.symbolid INNER JOIN symbols s ON bmr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON bmr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on bmr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_bigmovement_results rbr ON rbr.resultuid = bmr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bmr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (bmr.simulation = 0 OR bmr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('400' = 0 OR bmr.patternlengthbars <= '400') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, interval DESC;
Date: 2025-03-31 05:51:17 Duration: 413ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
11 21s556ms 16 1s247ms 1s463ms 1s347ms with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = ? left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bg.brokerid and bim.type = ? where bg.brokerid = ? and basegroupname = ? and g.designation = ? and s.nonliquid = ? ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = ? and cp.direction > ? and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = ? and cp.direction > ? and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = ? and cp.direction < ? and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = ? and cp.direction < ? and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = ? and cp.direction > ? and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = ? and cp.direction > ? and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = ? and cp.direction < ? and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = ? and cp.direction < ? and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval ?) as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= ? and patternquality >= ?.? and patternendtime >= current_timestamp - interval ? and patternlengthbars < ?) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval ?) as predictiontimefrom, predictionpricefrom, case when direction > ? then ? else ? end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (...) and patternendtime >= current_timestamp - interval ? and patternlengthbars < ?) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= ? and _tmp.qtycandlesapart <= ? and ((cpresultuid > ( select coalesce(max(cpresultuid), ?) from correlating_signals acs where acs.basegroupname = ? and acs.brokerid = ?)) or (klresultuid > ( select coalesce(max(klresultuid), ?) from correlating_signals acs where acs.basegroupname = ? and acs.brokerid = ?))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = ? and cs.basegroupname = ? and date_trunc(?, cs.gmttimefound) = date_trunc(?, now()) and sent is true and filtered is false ) <= ( select case when coalesce(daily_max, ?) < ? then ? else coalesce(daily_max,?) end from corr_sigs_config_v where broker_id = ? ) and extract(epoch from age(current_timestamp at time zone ?, max_patternendtime - absolutetimezoneoffset * interval ?))/? < mint*? ), maxstats as ( select max(statsid) as maxid , st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = ? then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * ? as numeric), ?) as percent, round(cast((kl_correct) / (kl_total) * ? as numeric), ?) as klpercent, round(cast((cp_correct ) / (cp_total ) * ? as numeric), ?) as cppercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), ?) as openprice, round(cast(sig.forecastprice as numeric), ?) as forecastprice, cast(round(cast(abs(sig.forecastprice - sig.openprice)/pip as numeric), ?)as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname , si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = ? then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = ? and date_part(?, sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = ? and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = ? and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = ? and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = ? and date_part(?, sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = ? and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = ? and kl_sym.name ilike si.symbol ) as tmp order by tmp.gmttimefound desc;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Mar 31 05 16 21s556ms 1s347ms [ User: postgres - Total duration: 21s556ms - Times executed: 16 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 21s556ms - Times executed: 16 ]
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with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '692' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '692')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '692'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '692' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '692') and extract(epoch from age(current_timestamp at TIME ZONE 'utc', max_patternendtime - absolutetimezoneoffset * INTERVAL '1 hour')) / 60 < mint * 3 ), maxstats as ( select MAX(statsid) as maxid, st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = 'exchange' then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * 100 as numeric), 2) as percent, round(cast((kl_correct) / (kl_total) * 100 as numeric), 2) as klPercent, round(cast((cp_correct) / (cp_total) * 100 as numeric), 2) as cpPercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), 5) as openprice, round(cast(sig.forecastprice as numeric), 5) as forecastprice, CAST(round(cast(abs(sig.forecastprice - sig.openprice) / pip as numeric), 0) as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname, si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = 'exchange' then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = 'hourofday' and date_part('hour', sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = 'interval' and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = 'pattern' and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = 'symbol' and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = 'hourofday' and date_part('hour', sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = 'interval' and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = 'symbol' and kl_sym.name ilike si.symbol) AS tmp order by tmp.gmttimefound desc;
Date: 2025-03-31 05:07:00 Duration: 1s463ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
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with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '617' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '617')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '617'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '617' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '617') and extract(epoch from age(current_timestamp at TIME ZONE 'utc', max_patternendtime - absolutetimezoneoffset * INTERVAL '1 hour')) / 60 < mint * 3 ), maxstats as ( select MAX(statsid) as maxid, st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = 'exchange' then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * 100 as numeric), 2) as percent, round(cast((kl_correct) / (kl_total) * 100 as numeric), 2) as klPercent, round(cast((cp_correct) / (cp_total) * 100 as numeric), 2) as cpPercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), 5) as openprice, round(cast(sig.forecastprice as numeric), 5) as forecastprice, CAST(round(cast(abs(sig.forecastprice - sig.openprice) / pip as numeric), 0) as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname, si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = 'exchange' then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = 'hourofday' and date_part('hour', sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = 'interval' and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = 'pattern' and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = 'symbol' and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = 'hourofday' and date_part('hour', sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = 'interval' and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = 'symbol' and kl_sym.name ilike si.symbol) AS tmp order by tmp.gmttimefound desc;
Date: 2025-03-31 05:21:48 Duration: 1s459ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
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with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '692' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '692')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '692'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '692' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '692') and extract(epoch from age(current_timestamp at TIME ZONE 'utc', max_patternendtime - absolutetimezoneoffset * INTERVAL '1 hour')) / 60 < mint * 3 ), maxstats as ( select MAX(statsid) as maxid, st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = 'exchange' then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * 100 as numeric), 2) as percent, round(cast((kl_correct) / (kl_total) * 100 as numeric), 2) as klPercent, round(cast((cp_correct) / (cp_total) * 100 as numeric), 2) as cpPercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), 5) as openprice, round(cast(sig.forecastprice as numeric), 5) as forecastprice, CAST(round(cast(abs(sig.forecastprice - sig.openprice) / pip as numeric), 0) as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname, si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = 'exchange' then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = 'hourofday' and date_part('hour', sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = 'interval' and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = 'pattern' and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = 'symbol' and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = 'hourofday' and date_part('hour', sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = 'interval' and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = 'symbol' and kl_sym.name ilike si.symbol) AS tmp order by tmp.gmttimefound desc;
Date: 2025-03-31 05:52:02 Duration: 1s445ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
12 19s500ms 336 0ms 254ms 58ms select distinct a.resultuid as ruid, c.symbolid as sid, c.symbol as sym, c.longname as longname, c.shortname, c.exchange as e, c.timegranularity as tg, p.patternid as pid, a.direction as d, cast(atbaridentified as timestamp) as pet, cast(patternstarttime as timestamp) as pst, patternprice as patp, breakoutprice as pe, breakoutbars as be, errormargin as erm, patternlengthbars as l, bandwidth as bw, qtytp as qtp, p.patternname as patternname, cast(x0 as timestamp) as x0, cast(x1 as timestamp) as x1, cast(x2 as timestamp) as x2, cast(( case when x3 = ? then ? else x3 end) as timestamp) as x3, cast(( case when x4 = ? then ? else x4 end) as timestamp) as x4, cast(( case when x5 = ? then ? else x5 end) as timestamp) as x5, cast(( case when x6 = ? then ? else x6 end) as timestamp) as x6, cast(( case when x7 = ? then ? else x7 end) as timestamp) as x7, cast(( case when x8 = ? then ? else x8 end) as timestamp) as x8, cast(( case when x9 = ? then ? else x9 end) as timestamp) as x9, cast(atbaridentified as timestamp) as patternendtime, cast(atbaridentified as timestamp) as atbar, cast(( case when approachingtimestamp = ? then ? else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzos, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, case when rar.age is not null then rar.age when a.resultuid <= ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) then ? else ? end as relevant, cast(?.? as double precision) as premium, cast(? as bigint) as instrumentid, ? as derivativeid, ? as underlyingid, ? as isunderlying from symbols c inner join brokersymbollist b on c.symbolid = b.symbolid inner join symbolgroup sg on c.symbolid = sg.symbolid inner join downloadersymbolsettings dss on dss.symbolid = c.symbolid inner join datafeedstimetable dftt on dftt.classname = dss.classname inner join keylevels_results a on a.symbolid = c.symbolid inner join hrspatterns p on a.patternid = p.patternid left outer join relevance_keylevels_results rar on rar.resultuid = a.resultuid where b.brokerid = ? and sg.groupid = ? and patternclassid = ? and patternlengthbars >= ? and a.patternid & ? > ? and dftt.dayofweek = ? and a.qtytp >= ? and a.resultuid > ? and c.nonliquid = ? and c.deleted = ? and dss.enabled = ? order by relevant desc, age asc, patternendtime desc, qtp desc limit ?;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Mar 31 05 336 19s500ms 58ms [ User: postgres - Total duration: 19s500ms - Times executed: 336 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 19s500ms - Times executed: 336 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059758978308 AND patternclassid = '2' AND patternlengthbars >= '20' AND a.PatternID & '39' > 0 AND dftt.dayofweek = '3' AND a.qtytp >= '0' AND a.resultuid > '-919550705' AND c.nonliquid = '0' AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:16:05 Duration: 254ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059718346308 AND patternclassid = '2' AND patternlengthbars >= '20' AND a.PatternID & '39' > 0 AND dftt.dayofweek = '3' AND a.qtytp >= '0' AND a.resultuid > '-628120145' AND c.nonliquid = '0' AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:32:06 Duration: 252ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059718346308 AND patternclassid = '2' AND patternlengthbars >= '20' AND a.PatternID & '39' > 0 AND dftt.dayofweek = '3' AND a.qtytp >= '0' AND a.resultuid > '-628120145' AND c.nonliquid = '0' AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:16:05 Duration: 248ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
13 19s355ms 17,065 0ms 17ms 1ms 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 #13
Day Hour Count Duration Avg duration Mar 31 05 17,065 19s355ms 1ms [ User: postgres - Total duration: 19s355ms - Times executed: 17065 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 19s355ms - Times executed: 17065 ]
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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 = '529' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '529' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840249421399300';
Date: 2025-03-31 05:30:04 Duration: 17ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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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 = '558' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '558' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840243225790300';
Date: 2025-03-31 05:00:04 Duration: 15ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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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 = '558' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '558' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840243266602300';
Date: 2025-03-31 05:00:04 Duration: 15ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
14 14s119ms 16 578ms 1s159ms 882ms 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;Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Mar 31 05 16 14s119ms 882ms [ User: postgres - Total duration: 14s119ms - Times executed: 16 ]
[ Application: psql - Total duration: 14s119ms - Times executed: 16 ]
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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: 2025-03-31 05:56:13 Duration: 1s159ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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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: 2025-03-31 05:11:12 Duration: 1s40ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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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: 2025-03-31 05:18:12 Duration: 1s27ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
15 13s233ms 177 15ms 367ms 74ms select distinct k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid from relevance_keylevels_results p inner join keylevels_results k on p.resultuid = k.resultuid inner join autochartist_stocklist asl on k.symbolid = asl.symbolid where k.patternclassid in (...) and asl.enabled = ? and asl.recognitionengine ilike ?;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Mar 31 05 177 13s233ms 74ms [ User: postgres - Total duration: 13s233ms - Times executed: 177 ]
[ Application: [unknown] - Total duration: 13s233ms - Times executed: 177 ]
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SELECT DISTINCT k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid FROM relevance_keylevels_results p INNER JOIN keylevels_results k ON p.resultuid = k.resultuid INNER JOIN autochartist_stocklist asl ON k.symbolid = asl.symbolid WHERE k.patternclassid in (1, 2) AND asl.enabled = 1 AND asl.recognitionengine ILIKE 'ATFX - 1';
Date: 2025-03-31 05:31:01 Duration: 367ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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SELECT DISTINCT k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid FROM relevance_keylevels_results p INNER JOIN keylevels_results k ON p.resultuid = k.resultuid INNER JOIN autochartist_stocklist asl ON k.symbolid = asl.symbolid WHERE k.patternclassid in (1, 2) AND asl.enabled = 1 AND asl.recognitionengine ILIKE 'ICMARKETS - 1';
Date: 2025-03-31 05:16:00 Duration: 260ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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SELECT DISTINCT k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid FROM relevance_keylevels_results p INNER JOIN keylevels_results k ON p.resultuid = k.resultuid INNER JOIN autochartist_stocklist asl ON k.symbolid = asl.symbolid WHERE k.patternclassid in (1, 2) AND asl.enabled = 1 AND asl.recognitionengine ILIKE 'ATFX - 1';
Date: 2025-03-31 05:06:18 Duration: 242ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
16 11s902ms 34 12ms 3s907ms 350ms select fixcandlegaps (?, false);Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Mar 31 05 34 11s902ms 350ms [ User: postgres - Total duration: 11s902ms - Times executed: 34 ]
[ Application: psql - Total duration: 11s902ms - Times executed: 34 ]
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select fixcandlegaps ('ICMARKETS-AU-MT5', false);
Date: 2025-03-31 05:06:14 Duration: 3s907ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('ATFX', false);
Date: 2025-03-31 05:06:05 Duration: 1s258ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('PEPPERSTONE', false);
Date: 2025-03-31 05:06:08 Duration: 1s69ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
17 10s176ms 13 54ms 2s741ms 782ms copy ( select array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ?) as broker_ids, string_to_array(coalesce(replace(broker_symbol_mappings, ?, ?), ?), ?) as broker_symbol_mappings, replace(exchange, ?, ?) as exchange, symbol_id, replace(symbol, ?, ?) as symbol, replace(short_name, ?, ?) as short_name, replace(long_name, ?, ?) as long_name, interval, replace(timezone, ?, ?) as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ?) as search_groups, string_to_array(pattern_basegroupnames, ?) as base_groups, simulation, signal_levels_entry_level, signal_levels_stop_level, signal_levels_target_level, signal_levels_target_period, signal_levels_filtered from solr_fetch_results (?::character varying, current_timestamp::timestamp without time zone)) t) to ?;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Mar 31 05 13 10s176ms 782ms [ User: postgres - Total duration: 10s176ms - Times executed: 13 ]
[ Application: psql - Total duration: 10s176ms - Times executed: 13 ]
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COPY ( select /*_solr_fetch_results__*/ array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ',') as broker_ids, string_to_array(COALESCE(replace(broker_symbol_mappings, '"', ''), ''), ',') as broker_symbol_mappings, replace(exchange, '"', '') as exchange,symbol_id,replace(symbol,'"','') as symbol, replace(short_name, '"', '') as short_name,replace(long_name,'"','') as long_name, interval, replace(timezone, '"', '') as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ',') as search_groups, string_to_array(pattern_basegroupnames, ',') as base_groups, simulation, signal_levels_entry_level, signal_levels_stop_level, signal_levels_target_level, signal_levels_target_period, signal_levels_filtered from solr_fetch_results ('Autochartist'::character varying, current_timestamp::timestamp without time zone)) t) TO '/tmp/solr_inserts_acaweb_fx.json';
Date: 2025-03-31 05:18:05 Duration: 2s741ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: psql
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COPY ( select /*_solr_fetch_results__*/ array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ',') as broker_ids, string_to_array(COALESCE(replace(broker_symbol_mappings, '"', ''), ''), ',') as broker_symbol_mappings, replace(exchange, '"', '') as exchange,symbol_id,replace(symbol,'"','') as symbol, replace(short_name, '"', '') as short_name,replace(long_name,'"','') as long_name, interval, replace(timezone, '"', '') as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ',') as search_groups, string_to_array(pattern_basegroupnames, ',') as base_groups, simulation, signal_levels_entry_level, signal_levels_stop_level, signal_levels_target_level, signal_levels_target_period, signal_levels_filtered from solr_fetch_results ('Autochartist'::character varying, current_timestamp::timestamp without time zone)) t) TO '/tmp/solr_inserts_acaweb_fx.json';
Date: 2025-03-31 05:33:04 Duration: 2s733ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: psql
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COPY ( select /*_solr_fetch_results__*/ array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ',') as broker_ids, string_to_array(COALESCE(replace(broker_symbol_mappings, '"', ''), ''), ',') as broker_symbol_mappings, replace(exchange, '"', '') as exchange,symbol_id,replace(symbol,'"','') as symbol, replace(short_name, '"', '') as short_name,replace(long_name,'"','') as long_name, interval, replace(timezone, '"', '') as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ',') as search_groups, string_to_array(pattern_basegroupnames, ',') as base_groups, simulation, signal_levels_entry_level, signal_levels_stop_level, signal_levels_target_level, signal_levels_target_period, signal_levels_filtered from solr_fetch_results ('Autochartist'::character varying, current_timestamp::timestamp without time zone)) t) TO '/tmp/solr_inserts_acaweb_fx.json';
Date: 2025-03-31 05:48:05 Duration: 2s340ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: psql
18 9s349ms 6 1s74ms 1s837ms 1s558ms refresh materialized view concurrently latest_t15_candle_view;Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Mar 31 05 6 9s349ms 1s558ms [ User: postgres - Total duration: 9s349ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 9s349ms - Times executed: 6 ]
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refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-03-31 05:16:18 Duration: 1s837ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
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refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-03-31 05:31:18 Duration: 1s808ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
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refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-03-31 05:01:17 Duration: 1s783ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
19 8s790ms 13 40ms 7s418ms 676ms copy ( select array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ?) as broker_ids, string_to_array(coalesce(replace(broker_symbol_mappings, ?, ?), ?), ?) as broker_symbol_mappings, replace(exchange, ?, ?) as exchange, symbol_id, replace(symbol, ?, ?) as symbol, replace(short_name, ?, ?) as short_name, replace(long_name, ?, ?) as long_name, interval, replace(timezone, ?, ?) as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ?) as search_groups, string_to_array(pattern_basegroupnames, ?) as base_groups, simulation from solr_fetch_results_bm_and_cc (?::character varying, current_timestamp::timestamp without time zone)) t) to ?;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Mar 31 05 13 8s790ms 676ms [ User: postgres - Total duration: 8s790ms - Times executed: 13 ]
[ Application: psql - Total duration: 8s790ms - Times executed: 13 ]
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COPY ( select /*_solr_fetch_results_bm_and_cc_*/ array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ',') as broker_ids, string_to_array(COALESCE(replace(broker_symbol_mappings, '"', ''), ''), ',') as broker_symbol_mappings, replace(exchange, '"', '') as exchange,symbol_id,replace(symbol,'"','') as symbol, replace(short_name, '"', '') as short_name,replace(long_name,'"','') as long_name, interval, replace(timezone, '"', '') as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ',') as search_groups, string_to_array(pattern_basegroupnames, ',') as base_groups, simulation from solr_fetch_results_bm_and_cc ('Autochartist'::character varying, current_timestamp::timestamp without time zone)) t) TO '/tmp/solr_inserts_bm_and_cc_acaweb_fx.json';
Date: 2025-03-31 05:03:09 Duration: 7s418ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: psql
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COPY ( select /*_solr_fetch_results_bm_and_cc_*/ array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ',') as broker_ids, string_to_array(COALESCE(replace(broker_symbol_mappings, '"', ''), ''), ',') as broker_symbol_mappings, replace(exchange, '"', '') as exchange,symbol_id,replace(symbol,'"','') as symbol, replace(short_name, '"', '') as short_name,replace(long_name,'"','') as long_name, interval, replace(timezone, '"', '') as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ',') as search_groups, string_to_array(pattern_basegroupnames, ',') as base_groups, simulation from solr_fetch_results_bm_and_cc ('Autochartist'::character varying, current_timestamp::timestamp without time zone)) t) TO '/tmp/solr_inserts_bm_and_cc_acaweb_fx.json';
Date: 2025-03-31 05:16:02 Duration: 379ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: psql
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COPY ( select /*_solr_fetch_results_bm_and_cc_*/ array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ',') as broker_ids, string_to_array(COALESCE(replace(broker_symbol_mappings, '"', ''), ''), ',') as broker_symbol_mappings, replace(exchange, '"', '') as exchange,symbol_id,replace(symbol,'"','') as symbol, replace(short_name, '"', '') as short_name,replace(long_name,'"','') as long_name, interval, replace(timezone, '"', '') as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ',') as search_groups, string_to_array(pattern_basegroupnames, ',') as base_groups, simulation from solr_fetch_results_bm_and_cc ('Autochartist'::character varying, current_timestamp::timestamp without time zone)) t) TO '/tmp/solr_inserts_bm_and_cc_acaweb_fx.json';
Date: 2025-03-31 05:11:02 Duration: 289ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: psql
20 7s812ms 177 15ms 166ms 44ms select distinct a.symbolid, p.resultuid, case when a.breakout >= ? then ? else ? end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient from relevance_autochartist_results p inner join autochartist_results a on p.resultuid = a.resultuid inner join autochartist_stocklist asl on a.symbolid = asl.symbolid where asl.enabled = ? and asl.recognitionengine ilike ?;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Mar 31 05 177 7s812ms 44ms [ User: postgres - Total duration: 7s812ms - Times executed: 177 ]
[ Application: [unknown] - Total duration: 7s812ms - Times executed: 177 ]
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SELECT distinct a.symbolid, p.resultuid, case when a.breakout >= 0 then 1 else 2 end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient FROM relevance_autochartist_results p INNER JOIN autochartist_results a ON p.resultuid = a.resultuid INNER JOIN autochartist_stocklist asl ON a.symbolid = asl.symbolid WHERE asl.enabled = 1 AND asl.recognitionengine ILIKE 'ICMARKETS - 1';
Date: 2025-03-31 05:16:00 Duration: 166ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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SELECT distinct a.symbolid, p.resultuid, case when a.breakout >= 0 then 1 else 2 end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient FROM relevance_autochartist_results p INNER JOIN autochartist_results a ON p.resultuid = a.resultuid INNER JOIN autochartist_stocklist asl ON a.symbolid = asl.symbolid WHERE asl.enabled = 1 AND asl.recognitionengine ILIKE 'ICMARKETS - 1';
Date: 2025-03-31 05:45:57 Duration: 165ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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SELECT distinct a.symbolid, p.resultuid, case when a.breakout >= 0 then 1 else 2 end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient FROM relevance_autochartist_results p INNER JOIN autochartist_results a ON p.resultuid = a.resultuid INNER JOIN autochartist_stocklist asl ON a.symbolid = asl.symbolid WHERE asl.enabled = 1 AND asl.recognitionengine ILIKE 'ICMARKETS - 1';
Date: 2025-03-31 05:17:09 Duration: 165ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
Most frequent queries (N)
Rank Times executed Total duration Min duration Max duration Avg duration Query 1 25,457 114ms 0ms 14ms 0ms select ?;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Mar 31 05 25,457 114ms 0ms [ User: postgres - Total duration: 114ms - Times executed: 25457 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 101ms - Times executed: 25203 ]
[ Application: [unknown] - Total duration: 13ms - Times executed: 254 ]
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select 1;
Date: 2025-03-31 05:30:05 Duration: 14ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT 1;
Date: 2025-03-31 05:52:02 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.0.114 Application: [unknown]
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SELECT 1;
Date: 2025-03-31 05:52:02 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.0.114 Application: [unknown]
2 17,065 19s355ms 0ms 17ms 1ms 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 Mar 31 05 17,065 19s355ms 1ms [ User: postgres - Total duration: 19s355ms - Times executed: 17065 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 19s355ms - Times executed: 17065 ]
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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 = '529' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '529' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840249421399300';
Date: 2025-03-31 05:30:04 Duration: 17ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
-
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 = '558' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '558' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840243225790300';
Date: 2025-03-31 05:00:04 Duration: 15ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
-
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 = '558' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '558' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840243266602300';
Date: 2025-03-31 05:00:04 Duration: 15ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
3 15,112 33s946ms 0ms 22ms 2ms select s.symbolid as id, s.symbol as name, s.exchange as exchange, s.timegranularity as interval, dtt.timezone as timezone from symbols s inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join brokersymbollist bsl on bsl.symbolid = s.symbolid where bsl.brokerid = ? and (? = ? or s.timegranularity = ?) and (s.symbol = ? or dss.downloadersymbol = ?) and dss.enabled = ?;Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Mar 31 05 15,112 33s946ms 2ms [ User: postgres - Total duration: 33s946ms - Times executed: 15112 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 33s946ms - Times executed: 15112 ]
-
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 = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '558' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'EURAUD' OR dss.downloadersymbol = 'EURAUD') AND dss.enabled = 1;
Date: 2025-03-31 05:00:04 Duration: 22ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
-
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 = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '558' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'AUDCAD' OR dss.downloadersymbol = 'AUDCAD') AND dss.enabled = 1;
Date: 2025-03-31 05:00:03 Duration: 20ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
-
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 = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'NZDCHF' OR dss.downloadersymbol = 'NZDCHF') AND dss.enabled = 1;
Date: 2025-03-31 05:30:06 Duration: 19ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
4 5,690 6s305ms 0ms 11ms 1ms 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 #4
Day Hour Count Duration Avg duration Mar 31 05 5,690 6s305ms 1ms [ User: postgres - Total duration: 6s305ms - Times executed: 5690 ]
[ Application: [unknown] - Total duration: 6s305ms - Times executed: 5690 ]
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-03-31 06:30:00', '8612.9', '8614.7', '8610', '8614.7', '299', '515840233377031300', '0', '2025-03-31 05:45:59.524', '2025-03-31 05:45:59.455') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '8612.9', high = '8614.7', low = '8610', close = '8614.7', volume = '299', bsf = '0', sastdatetimewritten = '2025-03-31 05:45:59.524', sastdatetimereceived = '2025-03-31 05:45:59.455';
Date: 2025-03-31 05:45:59 Duration: 11ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-03-31 06:15:00', '18.40951', '18.411', '18.40401', '18.40625', '440', '515840217624601300', '0', '2025-03-31 05:30:58.07', '2025-03-31 05:30:57.985') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '18.40951', high = '18.411', low = '18.40401', close = '18.40625', volume = '440', bsf = '0', sastdatetimewritten = '2025-03-31 05:30:58.07', sastdatetimereceived = '2025-03-31 05:30:57.985';
Date: 2025-03-31 05:30:58 Duration: 10ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-03-31 06:00:00', '103.785', '103.813', '103.777', '103.81', '1625', '515840245885978300', '0', '2025-03-31 05:15:33.799', '2025-03-31 05:15:33.635') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '103.785', high = '103.813', low = '103.777', close = '103.81', volume = '1625', bsf = '0', sastdatetimewritten = '2025-03-31 05:15:33.799', sastdatetimereceived = '2025-03-31 05:15:33.635';
Date: 2025-03-31 05:15:33 Duration: 9ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
5 5,000 189ms 0ms 9ms 0ms insert into sa_hist_consecutivecandles (symbolid, datetime, image, qty, percentile, direction, height) values (?, ?, null, ?, ?, ?, ?);Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Mar 31 05 5,000 189ms 0ms [ User: postgres - Total duration: 189ms - Times executed: 5000 ]
[ Application: [unknown] - Total duration: 189ms - Times executed: 5000 ]
-
insert into sa_hist_consecutivecandles (symbolid, datetime, image, qty, percentile, direction, height) values ('500991627550361200', '2025-03-31 05:00:00', NULL, '5', '0.95', '-1', '0.0012019500000000013');
Date: 2025-03-31 05:30:04 Duration: 9ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown] Bind query: yes
-
insert into sa_hist_consecutivecandles (symbolid, datetime, image, qty, percentile, direction, height) values ('500991628283528200', '2025-03-31 05:00:00', NULL, '4', '0.95', '-1', '0.2822933333333333');
Date: 2025-03-31 05:30:05 Duration: 4ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown] Bind query: yes
-
insert into sa_hist_consecutivecandles (symbolid, datetime, image, qty, percentile, direction, height) values ('500991628209882200', '2025-03-31 05:00:00', NULL, '4', '0.95', '-1', '0.017574783333333337');
Date: 2025-03-31 05:30:04 Duration: 3ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown] Bind query: yes
6 4,684 4s523ms 0ms 12ms 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 #6
Day Hour Count Duration Avg duration Mar 31 05 4,684 4s523ms 0ms [ User: postgres - Total duration: 4s523ms - Times executed: 4684 ]
[ Application: [unknown] - Total duration: 4s523ms - Times executed: 4684 ]
-
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 ('5158402432359393000.4138|45747.1354|45747.2188|45747.1771|45747.2292|18.4331|18.425|18.3785|18.3932', 515840243235939300, 2.000000000000000000000000000000, 'Pennant', 4, '2025-03-31 03:42:22'::timestamp without time zone, 1, 0.981615121587539496400000000000, 0.413812154696361511600000000000, 0.790438565340908949600000000000, 0.028465586943313168220000000000, 0.723989288052449442300000000000, 18.444773467798153630000000000000, 18.474318322715564730000000000000, '2025-03-31 06:30:00'::timestamp without time zone, '2025-03-31 08:07:30'::timestamp without time zone, '2025-03-31 00:00:00'::timestamp without time zone, '2025-03-31 06:30:00'::timestamp without time zone, 18.282399999999999100000000000000, 18.419924999999999220000000000000, '2025-03-31 03:15:00'::timestamp without time zone, '2025-03-31 05:15:00'::timestamp without time zone, '2025-03-31 04:15:00'::timestamp without time zone, '2025-03-31 05:30:00'::timestamp without time zone, 18.433119999999998840000000000000, 18.425000000000000710000000000000, 18.378499999999998950000000000000, 18.393190000000000600000000000000, 0.002938000000000329237000000000, - 0.001014999999999766089000000000, 4.400202739923570583000000000000, 0.772737744348259370000000000000, 'Continuation', 0.003745000000002107754000000000, '2025-03-31 06:30:00'::timestamp without time zone, 18.423670000000001320000000000000, 13, 0, 0.022155000000000295980000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-03-31 05:46:12 Duration: 12ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
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 ('515840243948250300-1|45741.875|45743.875|45743.6458|45744.875|7.4598|7.4601|7.4571|7.4576', 515840243948250300, 10.000000000000000000000000000000, 'Rising Wedge', 4, '2025-03-31 02:57:12'::timestamp without time zone, 1, 0.429674355301451538200000000000, - 1.000000000000000000000000000000, 0.521850307578087591000000000000, 0.255673604414283495200000000000, 0.460928498793178542700000000000, 7.459619368869859102000000000000, 7.460626485287662924000000000000, '2025-03-31 05:30:00'::timestamp without time zone, '2025-04-02 21:45:00'::timestamp without time zone, '2025-03-25 10:30:00'::timestamp without time zone, '2025-03-31 05:30:00'::timestamp without time zone, 7.456559999999999633000000000000, 7.459200000000000052000000000000, '2025-03-25 21:00:00'::timestamp without time zone, '2025-03-27 21:00:00'::timestamp without time zone, '2025-03-27 15:30:00'::timestamp without time zone, '2025-03-28 21:00:00'::timestamp without time zone, 7.459780000000000300000000000000, 7.460069999999999979000000000000, 7.457139999999999880000000000000, 7.457639999999999602000000000000, 0.000008474576271181744616000000, 0.000003020833333329993924000000, 2.197688287803032381000000000000, 0.544976416560115528600000000000, 'Continuation', 0.000000000000000000000000000000, '2025-03-31 05:30:00'::timestamp without time zone, 7.458899999999999864000000000000, 161, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-03-31 05:01:02 Duration: 11ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
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 ('5158402458609023000.1039|45729.125|45742.5417|45730|45737.75|0.5583|0.5593|0.5534|0.5527', 515840245860902300, 9.000000000000000000000000000000, 'Head and Shoulders', 5, '2025-03-31 02:57:21'::timestamp without time zone, - 1, 1.000000000000000000000000000000, 0.103904685444735675470000000000, 0.247497924887609022100000000000, 0.365653399906392673200000000000, 0.890568629757643726000000000000, 0.548200429506293662800000000000, 0.550486845627622400900000000000, '2025-03-31 05:00:00'::timestamp without time zone, '2025-04-09 06:00:00'::timestamp without time zone, '2025-03-11 04:00:00'::timestamp without time zone, '2025-03-31 05:00:00'::timestamp without time zone, 0.549270000000000036000000000000, 0.552160942028985468600000000000, '2025-03-13 03:00:00'::timestamp without time zone, '2025-03-26 13:00:00'::timestamp without time zone, '2025-03-14 00:00:00'::timestamp without time zone, '2025-03-21 18:00:00'::timestamp without time zone, 0.558320000000000038500000000000, 0.559259999999999979400000000000, 0.553350000000000008600000000000, 0.552740000000000009100000000000, - 0.000004420289855072459428000000, 0.000004159292035397968418000000, 2.917195228126034490000000000000, 0.657204978823996643900000000000, 'Reversal', - 0.000040942028985413436720000000, '2025-03-31 05:00:00'::timestamp without time zone, 0.552120000000000055200000000000, 290, 0, 0.003922499999999995435000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-03-31 05:01:10 Duration: 11ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
7 3,314 1s811ms 0ms 9ms 0ms insert into t30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Mar 31 05 3,314 1s811ms 0ms [ User: postgres - Total duration: 1s811ms - Times executed: 3314 ]
[ Application: [unknown] - Total duration: 1s811ms - Times executed: 3314 ]
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-03-31 06:00:00', '82.94', '83.08', '82.36', '82.73', '747', '515840247891126300', '0', '2025-03-31 05:30:59.319', '2025-03-31 05:30:59.124') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '82.94', high = '83.08', low = '82.36', close = '82.73', volume = '747', bsf = '0', sastdatetimewritten = '2025-03-31 05:30:59.319', sastdatetimereceived = '2025-03-31 05:30:59.124';
Date: 2025-03-31 05:30:59 Duration: 9ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-03-31 05:30:00', '0.62914', '0.62937', '0.62853', '0.62856', '1433', '515840247872890300', '0', '2025-03-31 05:00:42.805', '2025-03-31 05:00:42.662') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0.62914', high = '0.62937', low = '0.62853', close = '0.62856', volume = '1433', bsf = '0', sastdatetimewritten = '2025-03-31 05:00:42.805', sastdatetimereceived = '2025-03-31 05:00:42.662';
Date: 2025-03-31 05:00:42 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-03-31 06:00:00', '72.936', '72.976', '72.866', '72.916', '321', '515840248003773300', '0', '2025-03-31 05:30:48.969', '2025-03-31 05:30:48.905') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '72.936', high = '72.976', low = '72.866', close = '72.916', volume = '321', bsf = '0', sastdatetimewritten = '2025-03-31 05:30:48.969', sastdatetimereceived = '2025-03-31 05:30:48.905';
Date: 2025-03-31 05:30:48 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
8 2,861 16ms 0ms 0ms 0ms begin;Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Mar 31 05 2,861 16ms 0ms [ User: postgres - Total duration: 16ms - Times executed: 2861 ]
[ Application: [unknown] - Total duration: 16ms - Times executed: 2861 ]
-
BEGIN;
Date: 2025-03-31 05:30:08 Duration: 0ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown] Bind query: yes
-
BEGIN;
Date: 2025-03-31 05:52:02 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.0.114 Application: [unknown]
-
BEGIN;
Date: 2025-03-31 05:52:03 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.0.114 Application: [unknown]
9 2,838 2s941ms 0ms 6ms 1ms commit;Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Mar 31 05 2,838 2s941ms 1ms [ User: postgres - Total duration: 2s941ms - Times executed: 2838 ]
[ Application: [unknown] - Total duration: 2s941ms - Times executed: 2838 ]
-
COMMIT;
Date: 2025-03-31 05:30:05 Duration: 6ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown] Bind query: yes
-
COMMIT;
Date: 2025-03-31 05:30:05 Duration: 6ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown] Bind query: yes
-
COMMIT;
Date: 2025-03-31 05:30:05 Duration: 5ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown] Bind query: yes
10 2,236 1s197ms 0ms 7ms 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 #10
Day Hour Count Duration Avg duration Mar 31 05 2,236 1s197ms 0ms [ User: postgres - Total duration: 1s197ms - Times executed: 2236 ]
[ Application: [unknown] - Total duration: 1s197ms - Times executed: 2236 ]
-
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 (2.000000000000000000000000000000, 'Gartley', '2025-03-31 03:42:29'::timestamp without time zone, - 1, '2025-03-28 17:15:00'::timestamp without time zone, '2025-03-31 06:30:00'::timestamp without time zone, 0.617169999999999996400000000000, - 1.000000000000000000000000000000, 5, 0.617169999999999996400000000000, '2025-03-28 17:15:00'::timestamp without time zone, 0.612920000000000020400000000000, '2025-03-31 00:15:00'::timestamp without time zone, 0.615539999999999976000000000000, '2025-03-31 02:45:00'::timestamp without time zone, 0.613480000000000025300000000000, '2025-03-31 06:15:00'::timestamp without time zone, 0.616261143355649965200000000000, '1899-12-29 00:00:00'::timestamp without time zone, 0.653301279289874248200000000000, - 1.000000000000000000000000000000, 4.316745969193741317000000000000, 57, 0.613480000000000025300000000000, 0.614542302234411086400000000000, 0.611761158878761146500000000000, 0.614074743674746459400000000000, 0.612723474359186837100000000000, 0.614870571677824995200000000000, 0.615198841121238904000000000000, 515840217720899300, 0.693397441420251503600000000000, 'BC=0.786*AB (0.786) ', 0, 'Gartley|-1|2025-03-28 17:15:00|0.61717|-1|5|57|BC=0.786*AB (0.786)|0|515840217720899300|2025-03-28 17:15:00|2025-03-31 00:15:00|2025-03-31 02:45:00|2025-03-31 06:15:00|1899-12-29 00:00:00', - 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-03-31 05:46:19 Duration: 7ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
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 (2.000000000000000000000000000000, 'Gartley', '2025-03-31 03:42:29'::timestamp without time zone, - 1, '2025-03-28 17:15:00'::timestamp without time zone, '2025-03-31 06:30:00'::timestamp without time zone, 0.617169999999999996400000000000, - 1.000000000000000000000000000000, 5, 0.617169999999999996400000000000, '2025-03-28 17:15:00'::timestamp without time zone, 0.612920000000000020400000000000, '2025-03-31 00:15:00'::timestamp without time zone, 0.615539999999999976000000000000, '2025-03-31 02:45:00'::timestamp without time zone, 0.613480000000000025300000000000, '2025-03-31 06:15:00'::timestamp without time zone, 0.616261143355649965200000000000, '1899-12-29 00:00:00'::timestamp without time zone, 0.653301279289874248200000000000, - 1.000000000000000000000000000000, 4.316745969193741317000000000000, 57, 0.613480000000000025300000000000, 0.614542302234411086400000000000, 0.611761158878761146500000000000, 0.614074743674746459400000000000, 0.612723474359186837100000000000, 0.614870571677824995200000000000, 0.615198841121238904000000000000, 515840217720899300, 0.693397441420251503600000000000, 'BC=0.786*AB (0.786) ', 0, 'Gartley|-1|2025-03-28 17:15:00|0.61717|-1|5|57|BC=0.786*AB (0.786)|0|515840217720899300|2025-03-28 17:15:00|2025-03-31 00:15:00|2025-03-31 02:45:00|2025-03-31 06:15:00|1899-12-29 00:00:00', - 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-03-31 05:46:19 Duration: 6ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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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 (3.000000000000000000000000000000, 'ABCD', '2025-03-31 03:26:41'::timestamp without time zone, 1, '2025-03-27 23:30:00'::timestamp without time zone, '2025-03-30 23:00:00'::timestamp without time zone, 0.898399999999999976400000000000, - 1.000000000000000000000000000000, 4, - 1.000000000000000000000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 0.902932863999999946200000000000, '2025-03-28 10:00:00'::timestamp without time zone, 0.893129999999999979400000000000, '2025-03-30 17:00:00'::timestamp without time zone, 0.901072281000000030400000000000, '2025-03-30 21:30:00'::timestamp without time zone, 0.891269417000000063800000000000, '1899-12-29 00:00:00'::timestamp without time zone, 0.714100245000336864000000000000, - 1.000000000000000000000000000000, 35.017911981646918210000000000000, 37, 0.901072281000000030400000000000, 0.897327920138603629600000000000, 0.907130784138603596400000000000, 0.898975952039986037100000000000, 0.903738852629376143700000000000, 0.896170848999999991600000000000, 0.895013777861396464600000000000, 515840249496512300, 0.571799509999326161000000000000, 'BC=0.786*AB (0.81) ', 0, 'ABCD|1|2025-03-27 23:30:00|0.8984|-1|4|37|BC=0.786*AB (0.81)|0|515840249496512300|1899-12-29 00:00:00|2025-03-28 10:00:00|2025-03-30 17:00:00|2025-03-30 21:30:00|1899-12-29 00:00:00', - 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-03-31 05:30:31 Duration: 6ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
11 2,236 1s7ms 0ms 8ms 0ms insert into t60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Mar 31 05 2,236 1s7ms 0ms [ User: postgres - Total duration: 1s7ms - Times executed: 2236 ]
[ Application: [unknown] - Total duration: 1s7ms - Times executed: 2236 ]
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-03-31 05:00:00', '0.95249', '0.95276', '0.95215', '0.95227', '3299', '515840247874906300', '0', '2025-03-31 05:00:53.011', '2025-03-31 05:00:52.928') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0.95249', high = '0.95276', low = '0.95215', close = '0.95227', volume = '3299', bsf = '0', sastdatetimewritten = '2025-03-31 05:00:53.011', sastdatetimereceived = '2025-03-31 05:00:52.928';
Date: 2025-03-31 05:00:53 Duration: 8ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-03-31 05:00:00', '0.62885', '0.62937', '0.62853', '0.62856', '3360', '515840247873079300', '0', '2025-03-31 05:00:42.842', '2025-03-31 05:00:42.759') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0.62885', high = '0.62937', low = '0.62853', close = '0.62856', volume = '3360', bsf = '0', sastdatetimewritten = '2025-03-31 05:00:42.842', sastdatetimereceived = '2025-03-31 05:00:42.759';
Date: 2025-03-31 05:00:42 Duration: 8ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-03-31 05:00:00', '0.5575', '0.5585', '0.5475', '0.5495', '213', '515840247923246300', '0', '2025-03-31 05:00:48.834', '2025-03-31 05:00:48.753') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0.5575', high = '0.5585', low = '0.5475', close = '0.5495', volume = '213', bsf = '0', sastdatetimewritten = '2025-03-31 05:00:48.834', sastdatetimereceived = '2025-03-31 05:00:48.753';
Date: 2025-03-31 05:00:48 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
12 1,844 996ms 0ms 7ms 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 Mar 31 05 1,844 996ms 0ms [ User: postgres - Total duration: 996ms - Times executed: 1844 ]
[ Application: [unknown] - Total duration: 996ms - Times executed: 1844 ]
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UPDATE patternresultsrelevance SET relevant = 0, saxo_relevant = 0, notrelevantpricedatetime = '2025-03-31 05:30:00', reason = 'Pattern is too old to be relevant.' WHERE uniqueIndex = '|515840217678571300|167.962|2|2025-03-31 00:30:00|2025-03-31 00:30:00|-1|-1' and relevant = 1;
Date: 2025-03-31 05:31:14 Duration: 7ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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UPDATE patternresultsrelevance SET relevant = 0, saxo_relevant = 0, notrelevantpricedatetime = '2025-03-31 05:30:00', reason = 'Price has moved too far in the wrong direction' WHERE uniqueIndex = '|515840243226117300|10.50093|1|2025-03-31 04:30:00|2025-03-31 04:30:00|1|-1' and relevant = 1;
Date: 2025-03-31 05:02:05 Duration: 6ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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UPDATE patternresultsrelevance SET relevant = 0, saxo_relevant = 0, notrelevantpricedatetime = '2025-03-31 05:30:00', reason = 'Price has moved too far in the wrong direction' WHERE uniqueIndex = '|515840230625412300|33.4785|2|2025-03-31 03:30:00|2025-03-31 03:30:00|-1|-1' and relevant = 1;
Date: 2025-03-31 05:01:12 Duration: 3ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
13 1,561 3s382ms 0ms 13ms 2ms select * from ( select pricedatetime as datetime, open as open, high as high, low as low, close "..." close, volume as volume from t240 where symbolid = ? order by pricedatetime desc limit ?) as tmp order by datetime asc;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Mar 31 05 1,561 3s382ms 2ms [ User: postgres - Total duration: 3s382ms - Times executed: 1561 ]
[ Application: [unknown] - Total duration: 3s382ms - Times executed: 1561 ]
-
select * from ( select pricedatetime as DateTime, open as Open, high as High, low as Low, close as Close, volume as Volume from T240 where symbolid = 500991628282619200 order by pricedatetime desc limit 600) as tmp order by datetime asc;
Date: 2025-03-31 05:30:05 Duration: 13ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown] Bind query: yes
-
select * from ( select pricedatetime as DateTime, open as Open, high as High, low as Low, close as Close, volume as Volume from T240 where symbolid = 500991628280178200 order by pricedatetime desc limit 600) as tmp order by datetime asc;
Date: 2025-03-31 05:30:05 Duration: 12ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown] Bind query: yes
-
select * from ( select pricedatetime as DateTime, open as Open, high as High, low as Low, close as Close, volume as Volume from T240 where symbolid = 515840216970544300 order by pricedatetime desc limit 600) as tmp order by datetime asc;
Date: 2025-03-31 05:30:05 Duration: 10ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown] Bind query: yes
14 1,506 2s586ms 0ms 20ms 1ms select * from ( select pricedatetime as datetime, open as open, high as high, low as low, close "..." close, volume as volume from t60 where symbolid = ? order by pricedatetime desc limit ?) as tmp order by datetime asc;Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Mar 31 05 1,506 2s586ms 1ms [ User: postgres - Total duration: 2s586ms - Times executed: 1506 ]
[ Application: [unknown] - Total duration: 2s586ms - Times executed: 1506 ]
-
select * from ( select pricedatetime as DateTime, open as Open, high as High, low as Low, close as Close, volume as Volume from T60 where symbolid = 500991628285625200 order by pricedatetime desc limit 600) as tmp order by datetime asc;
Date: 2025-03-31 05:30:05 Duration: 20ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown] Bind query: yes
-
select * from ( select pricedatetime as DateTime, open as Open, high as High, low as Low, close as Close, volume as Volume from T60 where symbolid = 515840216585127300 order by pricedatetime desc limit 600) as tmp order by datetime asc;
Date: 2025-03-31 05:30:05 Duration: 20ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown] Bind query: yes
-
select * from ( select pricedatetime as DateTime, open as Open, high as High, low as Low, close as Close, volume as Volume from T60 where symbolid = 515840221147170300 order by pricedatetime desc limit 600) as tmp order by datetime asc;
Date: 2025-03-31 05:30:06 Duration: 20ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown] Bind query: yes
15 1,379 2s430ms 0ms 9ms 1ms 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 #15
Day Hour Count Duration Avg duration Mar 31 05 1,379 2s430ms 1ms [ User: postgres - Total duration: 2s430ms - Times executed: 1379 ]
[ Application: [unknown] - Total duration: 2s430ms - Times executed: 1379 ]
-
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 (5.000000000000000000000000000000, - 1, 1, '2025-03-31 03:42:23'::timestamp without time zone, '2025-03-31 06:30:00', 0.022530000000000108970000000000, 5, 138, 10.018200000000000216000000000000, '2025-03-28 23:45:00', '2025-03-28 10:00:00', '2025-03-28 08:45:00', '2025-03-28 07:15:00', '2025-03-27 20:00:00', '', '', '', '', '', 332, 10.022589500000000484000000000000, '2025-03-31 06:30:00'::timestamp without time zone, '2025-03-31 06:30:00', 9.998160000000000380000000000000, 0.004389500000000000172000000000, 1, 515840243231237300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840243231237300|10.0182|1|2025-03-31 06:30:00|2025-03-31 06:30:00|1|-1', 9.987108600000000891000000000000, 0.031091399999999325130000000000, 2, '2025-03-27 20:00:00', 9.983200000000000074000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-03-31 05:46:13 Duration: 9ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
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 (7.000000000000000000000000000000, - 1, 1, '2025-03-31 03:12:10'::timestamp without time zone, '2025-03-31 06:00:00', 0.000644999999999956155300000000, 4, 217, 1.340109999999999912000000000000, '2025-03-28 03:30:00', '2025-03-27 16:15:00', '2025-03-27 11:00:00', '2025-03-26 23:45:00', '', '', '', '', '', '', 277, 1.340307499999999985000000000000, '2025-03-31 06:00:00'::timestamp without time zone, '2025-03-31 06:00:00', 1.339730000000000088000000000000, 0.000197500000000005993200000000, 1, 515840243941320300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840243941320300|1.34011|1|2025-03-31 06:00:00|2025-03-31 06:00:00|1|-1', 1.339219900000000019000000000000, 0.000890099999999893754000000000, 2, '2025-03-26 23:45:00', 1.338449999999999918000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-03-31 05:16:00 Duration: 8ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
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 (7.000000000000000000000000000000, - 1, 1, '2025-03-31 03:26:26'::timestamp without time zone, '', 0.500000000000000000000000000000, 3, 172, 12.962580000000000880000000000000, '2025-03-31 01:00:00', '2025-03-27 09:00:00', '2025-03-27 06:00:00', '', '', '', '', '', '', '', 344, 12.969422500000000300000000000000, '2025-03-31 06:15:00'::timestamp without time zone, '2025-03-31 06:15:00', 0.000000000000000000000000000000, 0.006842499999999951920000000000, - 1, 500991628227355200, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|500991628227355200|12.96258|1|2025-03-31 06:15:00|-1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2025-03-27 06:00:00', 13.026859999999999220000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-03-31 05:30:16 Duration: 8ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
16 1,030 9ms 0ms 0ms 0ms set extra_float_digits = ?;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Mar 31 05 1,030 9ms 0ms [ User: postgres - Total duration: 9ms - Times executed: 1030 ]
[ Application: [unknown] - Total duration: 9ms - Times executed: 1030 ]
-
SET extra_float_digits = 3;
Date: 2025-03-31 05:14:59 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: [unknown] Bind query: yes
-
SET extra_float_digits = 3;
Date: 2025-03-31 05:42:12 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: [unknown] Bind query: yes
-
SET extra_float_digits = 3;
Date: 2025-03-31 05:40:30 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: [unknown] Bind query: yes
17 998 14ms 0ms 0ms 0ms set application_name = ?;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Mar 31 05 998 14ms 0ms [ User: postgres - Total duration: 14ms - Times executed: 998 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 14ms - Times executed: 998 ]
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-03-31 05:00:04 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-03-31 05:52:05 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-03-31 05:04:04 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
18 629 774ms 0ms 20ms 1ms 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 #18
Day Hour Count Duration Avg duration Mar 31 05 629 774ms 1ms [ User: postgres - Total duration: 774ms - Times executed: 629 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 766ms - Times executed: 623 ]
[ Application: [unknown] - Total duration: 7ms - Times executed: 6 ]
-
WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ) 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 = '605863599164647301' 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 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM 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 1 = 1 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 = '605863599164647301' OR a.resultuid = '605863599164647301') AND dtt.dayofweek = 3;
Date: 2025-03-31 05:16:16 Duration: 20ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ) 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 = '605863597054740301' 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 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM 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 1 = 1 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 = '605863597054740301' OR a.resultuid = '605863597054740301') AND dtt.dayofweek = 3;
Date: 2025-03-31 05:16:16 Duration: 19ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ) 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 = '605863010932563301' 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 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM 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 1 = 1 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 = '605863010932563301' OR a.resultuid = '605863010932563301') AND dtt.dayofweek = 3;
Date: 2025-03-31 05:30:48 Duration: 9ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
19 612 177ms 0ms 3ms 0ms select case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as resultuid, s.symbol, pattern as patternname, timegranularity as interval, patternlengthbars as length, patternendtime, direction, breakout, predictiontimeto, predictionpricefrom, predictionpriceto, patternstartprice, resy1, supporty1, dtt.timezone, cps.pip, newlevels.profit from autochartist_results a inner join downloadersymbolsettings dss on a.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern left join currencypips cps on cps.symbol = s.symbol left join lateral calc_cp_signal (a.resultuid) newlevels on true where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Mar 31 05 612 177ms 0ms [ User: postgres - Total duration: 177ms - Times executed: 612 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 177ms - Times executed: 612 ]
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SELECT CASE WHEN a.old_resultuid = '605863367583880301' THEN a.old_resultuid ELSE a.resultuid END as resultuid, s.symbol, pattern as patternname, timegranularity as interval, patternlengthbars AS length, patternendtime, direction, breakout, predictiontimeto, predictionpricefrom, predictionpriceto, patternStartPrice, resy1, supporty1, dtt.timezone, cps.pip, newLevels.profit FROM autochartist_results a INNER JOIN downloadersymbolsettings dss ON a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname INNER JOIN symbols s ON a.symbolid = s.symbolid INNER JOIN patterns p ON p.patternname = a.pattern LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT JOIN LATERAL calc_cp_signal (a.resultuid) newLevels on true WHERE (a.old_resultuid = '605863367583880301' OR a.resultuid = '605863367583880301') AND dtt.dayofweek = 3;
Date: 2025-03-31 05:16:32 Duration: 3ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT CASE WHEN a.old_resultuid = '605863658844017301' THEN a.old_resultuid ELSE a.resultuid END as resultuid, s.symbol, pattern as patternname, timegranularity as interval, patternlengthbars AS length, patternendtime, direction, breakout, predictiontimeto, predictionpricefrom, predictionpriceto, patternStartPrice, resy1, supporty1, dtt.timezone, cps.pip, newLevels.profit FROM autochartist_results a INNER JOIN downloadersymbolsettings dss ON a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname INNER JOIN symbols s ON a.symbolid = s.symbolid INNER JOIN patterns p ON p.patternname = a.pattern LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT JOIN LATERAL calc_cp_signal (a.resultuid) newLevels on true WHERE (a.old_resultuid = '605863658844017301' OR a.resultuid = '605863658844017301') AND dtt.dayofweek = 3;
Date: 2025-03-31 05:56:00 Duration: 3ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT CASE WHEN a.old_resultuid = '605863718639294301' THEN a.old_resultuid ELSE a.resultuid END as resultuid, s.symbol, pattern as patternname, timegranularity as interval, patternlengthbars AS length, patternendtime, direction, breakout, predictiontimeto, predictionpricefrom, predictionpriceto, patternStartPrice, resy1, supporty1, dtt.timezone, cps.pip, newLevels.profit FROM autochartist_results a INNER JOIN downloadersymbolsettings dss ON a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname INNER JOIN symbols s ON a.symbolid = s.symbolid INNER JOIN patterns p ON p.patternname = a.pattern LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT JOIN LATERAL calc_cp_signal (a.resultuid) newLevels on true WHERE (a.old_resultuid = '605863718639294301' OR a.resultuid = '605863718639294301') AND dtt.dayofweek = 3;
Date: 2025-03-31 05:46:58 Duration: 3ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
20 567 957ms 0ms 13ms 1ms 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 #20
Day Hour Count Duration Avg duration Mar 31 05 567 957ms 1ms [ User: postgres - Total duration: 957ms - Times executed: 567 ]
[ Application: [unknown] - Total duration: 957ms - Times executed: 567 ]
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol FROM downloadersymbolsettings dss INNER JOIN symbols s ON dss.symbolid = s.symbolid WHERE dss.classname = 'ICMARKETS-AU-MT5' AND s.deleted = 0 AND dss.enabled = 1;
Date: 2025-03-31 05:31:03 Duration: 13ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol FROM downloadersymbolsettings dss INNER JOIN symbols s ON dss.symbolid = s.symbolid WHERE dss.classname = 'ICMARKETS-AU-MT5' AND s.deleted = 0 AND dss.enabled = 1;
Date: 2025-03-31 05:30:59 Duration: 4ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol FROM downloadersymbolsettings dss INNER JOIN symbols s ON dss.symbolid = s.symbolid WHERE dss.classname = 'ICMARKETS-AU-MT5' AND s.deleted = 0 AND dss.enabled = 1;
Date: 2025-03-31 05:31:13 Duration: 4ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
Normalized slowest queries (N)
Rank Min duration Max duration Avg duration Times executed Total duration Query 1 11s22ms 11s523ms 11s258ms 4 45s32ms select updateageforrelevantresults ();Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Mar 31 05 4 45s32ms 11s258ms [ User: postgres - Total duration: 45s32ms - Times executed: 4 ]
[ Application: psql - Total duration: 45s32ms - Times executed: 4 ]
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select updateageforrelevantresults ();
Date: 2025-03-31 05:17:13 Duration: 11s523ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-03-31 05:32:14 Duration: 11s452ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-03-31 05:02:13 Duration: 11s33ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
2 407ms 24s93ms 8s610ms 346 49m39s with rar_max as ( select resultuid from relevance_autochartist_results order by resultuid desc limit ? ), ar as ( select a.*, rr.age, rr.relevant from autochartist_results a left outer join relevance_autochartist_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_autochartist_results) end ), all_results as ( select ar.resultuid as resultuid, ar.direction as direction, ar.predictiontimeto as predictiontimeto, ar.predictionpricefrom as predictionpricefrom, ar.predictionpriceto as predictionpriceto, cp.pip as pip, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ar.pattern as pattern_name, ar.breakout as breakout, ar.patternendtime as identified, dtt.timezone as timezone, ar.patternlengthbars as length, g.basegroupname, newlevels.profit, newlevels.stop, newlevels.filtered, case when ar.age is not null then ar.age when ar.resultuid <= rm.resultuid then ? else ? end as age, case when ar.relevant is not null then ar.relevant when ar.resultuid <= rm.resultuid then ? else ? end as relevant from ar inner join symbols s on ar.symbolid = s.symbolid and s.nonliquid = ? inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = s.symbolid inner join symbolgroup sg on bsl.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join downloadersymbolsettings dss on sg.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left outer join autochartist_symbolupdates au on dss.symbolid = au.symbolid left outer join currencypips cp on s.symbol = cp.symbol left join lateral calc_cp_signal (ar.resultuid) newlevels on true left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where ar.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (ar.simulation = ? or ar.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ar.pattern in (...)) and (? = ? or (? = ? and ar.breakout >= ?) or (? = ? and ar.breakout < ?)) and (? = ? or ar.patternlengthbars <= ?) and newlevels.filtered = false and ar.patternstarttime >= coalesce(au.earliestpricedatetime, ?::timestamp without time zone) -- to make sure patternstarttime is in our t-tables ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration Mar 31 05 346 49m39s 8s610ms [ User: postgres - Total duration: 49m39s - Times executed: 346 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 46m9s - Times executed: 334 ]
[ Application: [unknown] - Total duration: 3m29s - Times executed: 12 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-03-31 05:20:54 Duration: 24s93ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-03-31 05:00:50 Duration: 20s438ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-03-31 05:17:07 Duration: 18s465ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
3 172ms 38s424ms 8s315ms 345 47m48s 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 #3
Day Hour Count Duration Avg duration Mar 31 05 345 47m48s 8s315ms [ User: postgres - Total duration: 47m48s - Times executed: 345 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 44m7s - Times executed: 333 ]
[ Application: [unknown] - Total duration: 3m41s - Times executed: 12 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), 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 = 't' 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 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 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 = 3 INNER JOIN rar_max rm ON 1 = 1 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 = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-03-31 05:56:12 Duration: 38s424ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), 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 = 't' 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 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 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 = 3 INNER JOIN rar_max rm ON 1 = 1 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 = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-03-31 05:50:50 Duration: 36s195ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), 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 = 't' 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 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 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 = 3 INNER JOIN rar_max rm ON 1 = 1 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 = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-03-31 05:18:32 Duration: 35s480ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
4 4s669ms 6s476ms 5s449ms 6 32s697ms 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 = ?;Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Mar 31 05 6 32s697ms 5s449ms [ User: postgres - Total duration: 32s697ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 32s697ms - Times executed: 6 ]
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with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-03-31 05:30:09 Duration: 6s476ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
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with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-03-31 05:20:08 Duration: 5s807ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
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with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-03-31 05:00:08 Duration: 5s785ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
5 638ms 8s137ms 2s800ms 313 14m36s with rar_max as ( select resultuid from relevance_fibonacci_results order by resultuid desc limit ? ), fr as ( select a.*, rr.age, rr.relevant from fibonacci_results a left outer join relevance_fibonacci_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) end ), all_results as ( select fr.resultuid as resultuid, fr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, fr.pattern as pattern_name, fr.timed as timed, fr.patternendtime as identified, dtt.timezone as timezone, fr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when fr.age is not null then fr.age when fr.resultuid <= rm.resultuid then ? else ? end as age, case when fr.relevant is not null then fr.relevant when fr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from fr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = fr.symbolid inner join symbols s on fr.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on fr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join downloadersymbolsettings dss on fr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left join lateral calc_fib_signal_filter (fr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where fr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (fr.simulation = ? or fr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or fr.pattern in (...)) and (? = ? or fr.patternlengthbars <= ?) and (? = ? or (? = ? and fr.timed > cast(? as timestamp)) or (? = ? and fr.timed < cast(? as timestamp))) ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Mar 31 05 313 14m36s 2s800ms [ User: postgres - Total duration: 14m36s - Times executed: 313 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 13m31s - Times executed: 301 ]
[ Application: [unknown] - Total duration: 1m4s - Times executed: 12 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1 ), fr AS ( SELECT a.*, rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END ), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR fr.pattern in ('')) AND ('0' = 0 OR fr.patternlengthbars <= '0') AND ('0' = 0 OR ('0' = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ('0' = 2 AND fr.timed < cast('1970-01-01' as timestamp))) ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-03-31 05:17:11 Duration: 8s137ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1 ), fr AS ( SELECT a.*, rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END ), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR fr.pattern in ('')) AND ('400' = 0 OR fr.patternlengthbars <= '400') AND ('0' = 0 OR ('0' = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ('0' = 2 AND fr.timed < cast('1970-01-01' as timestamp))) ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-03-31 05:55:55 Duration: 8s131ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1 ), fr AS ( SELECT a.*, rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END ), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('0' = 0 OR fr.pattern in ('')) AND ('400' = 0 OR fr.patternlengthbars <= '400') AND ('0' = 0 OR ('0' = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ('0' = 2 AND fr.timed < cast('1970-01-01' as timestamp))) ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-03-31 05:17:14 Duration: 7s431ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
6 1s594ms 2s685ms 2s7ms 16 32s113ms 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;Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Mar 31 05 16 32s113ms 2s7ms [ User: postgres - Total duration: 32s113ms - Times executed: 16 ]
[ Application: psql - Total duration: 32s113ms - Times executed: 16 ]
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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: 2025-03-31 05:16:15 Duration: 2s685ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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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: 2025-03-31 05:26:16 Duration: 2s671ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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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: 2025-03-31 05:01:15 Duration: 2s631ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
7 1s74ms 1s837ms 1s558ms 6 9s349ms refresh materialized view concurrently latest_t15_candle_view;Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Mar 31 05 6 9s349ms 1s558ms [ User: postgres - Total duration: 9s349ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 9s349ms - Times executed: 6 ]
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refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-03-31 05:16:18 Duration: 1s837ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
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refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-03-31 05:31:18 Duration: 1s808ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
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refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-03-31 05:01:17 Duration: 1s783ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
8 1s247ms 1s463ms 1s347ms 16 21s556ms with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = ? left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bg.brokerid and bim.type = ? where bg.brokerid = ? and basegroupname = ? and g.designation = ? and s.nonliquid = ? ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = ? and cp.direction > ? and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = ? and cp.direction > ? and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = ? and cp.direction < ? and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = ? and cp.direction < ? and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = ? and cp.direction > ? and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = ? and cp.direction > ? and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = ? and cp.direction < ? and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = ? and cp.direction < ? and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval ?) as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= ? and patternquality >= ?.? and patternendtime >= current_timestamp - interval ? and patternlengthbars < ?) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval ?) as predictiontimefrom, predictionpricefrom, case when direction > ? then ? else ? end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (...) and patternendtime >= current_timestamp - interval ? and patternlengthbars < ?) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= ? and _tmp.qtycandlesapart <= ? and ((cpresultuid > ( select coalesce(max(cpresultuid), ?) from correlating_signals acs where acs.basegroupname = ? and acs.brokerid = ?)) or (klresultuid > ( select coalesce(max(klresultuid), ?) from correlating_signals acs where acs.basegroupname = ? and acs.brokerid = ?))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = ? and cs.basegroupname = ? and date_trunc(?, cs.gmttimefound) = date_trunc(?, now()) and sent is true and filtered is false ) <= ( select case when coalesce(daily_max, ?) < ? then ? else coalesce(daily_max,?) end from corr_sigs_config_v where broker_id = ? ) and extract(epoch from age(current_timestamp at time zone ?, max_patternendtime - absolutetimezoneoffset * interval ?))/? < mint*? ), maxstats as ( select max(statsid) as maxid , st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = ? then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * ? as numeric), ?) as percent, round(cast((kl_correct) / (kl_total) * ? as numeric), ?) as klpercent, round(cast((cp_correct ) / (cp_total ) * ? as numeric), ?) as cppercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), ?) as openprice, round(cast(sig.forecastprice as numeric), ?) as forecastprice, cast(round(cast(abs(sig.forecastprice - sig.openprice)/pip as numeric), ?)as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname , si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = ? then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = ? and date_part(?, sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = ? and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = ? and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = ? and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = ? and date_part(?, sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = ? and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = ? and kl_sym.name ilike si.symbol ) as tmp order by tmp.gmttimefound desc;Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Mar 31 05 16 21s556ms 1s347ms [ User: postgres - Total duration: 21s556ms - Times executed: 16 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 21s556ms - Times executed: 16 ]
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with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '692' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '692')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '692'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '692' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '692') and extract(epoch from age(current_timestamp at TIME ZONE 'utc', max_patternendtime - absolutetimezoneoffset * INTERVAL '1 hour')) / 60 < mint * 3 ), maxstats as ( select MAX(statsid) as maxid, st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = 'exchange' then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * 100 as numeric), 2) as percent, round(cast((kl_correct) / (kl_total) * 100 as numeric), 2) as klPercent, round(cast((cp_correct) / (cp_total) * 100 as numeric), 2) as cpPercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), 5) as openprice, round(cast(sig.forecastprice as numeric), 5) as forecastprice, CAST(round(cast(abs(sig.forecastprice - sig.openprice) / pip as numeric), 0) as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname, si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = 'exchange' then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = 'hourofday' and date_part('hour', sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = 'interval' and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = 'pattern' and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = 'symbol' and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = 'hourofday' and date_part('hour', sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = 'interval' and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = 'symbol' and kl_sym.name ilike si.symbol) AS tmp order by tmp.gmttimefound desc;
Date: 2025-03-31 05:07:00 Duration: 1s463ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
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with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '617' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '617')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '617'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '617' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '617') and extract(epoch from age(current_timestamp at TIME ZONE 'utc', max_patternendtime - absolutetimezoneoffset * INTERVAL '1 hour')) / 60 < mint * 3 ), maxstats as ( select MAX(statsid) as maxid, st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = 'exchange' then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * 100 as numeric), 2) as percent, round(cast((kl_correct) / (kl_total) * 100 as numeric), 2) as klPercent, round(cast((cp_correct) / (cp_total) * 100 as numeric), 2) as cpPercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), 5) as openprice, round(cast(sig.forecastprice as numeric), 5) as forecastprice, CAST(round(cast(abs(sig.forecastprice - sig.openprice) / pip as numeric), 0) as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname, si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = 'exchange' then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = 'hourofday' and date_part('hour', sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = 'interval' and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = 'pattern' and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = 'symbol' and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = 'hourofday' and date_part('hour', sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = 'interval' and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = 'symbol' and kl_sym.name ilike si.symbol) AS tmp order by tmp.gmttimefound desc;
Date: 2025-03-31 05:21:48 Duration: 1s459ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
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with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '692' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '692')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '692'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '692' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '692') and extract(epoch from age(current_timestamp at TIME ZONE 'utc', max_patternendtime - absolutetimezoneoffset * INTERVAL '1 hour')) / 60 < mint * 3 ), maxstats as ( select MAX(statsid) as maxid, st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = 'exchange' then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * 100 as numeric), 2) as percent, round(cast((kl_correct) / (kl_total) * 100 as numeric), 2) as klPercent, round(cast((cp_correct) / (cp_total) * 100 as numeric), 2) as cpPercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), 5) as openprice, round(cast(sig.forecastprice as numeric), 5) as forecastprice, CAST(round(cast(abs(sig.forecastprice - sig.openprice) / pip as numeric), 0) as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname, si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = 'exchange' then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = 'hourofday' and date_part('hour', sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = 'interval' and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = 'pattern' and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = 'symbol' and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = 'hourofday' and date_part('hour', sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = 'interval' and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = 'symbol' and kl_sym.name ilike si.symbol) AS tmp order by tmp.gmttimefound desc;
Date: 2025-03-31 05:52:02 Duration: 1s445ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
9 578ms 1s159ms 882ms 16 14s119ms 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;Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Mar 31 05 16 14s119ms 882ms [ User: postgres - Total duration: 14s119ms - Times executed: 16 ]
[ Application: psql - Total duration: 14s119ms - Times executed: 16 ]
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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: 2025-03-31 05:56:13 Duration: 1s159ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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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: 2025-03-31 05:11:12 Duration: 1s40ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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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: 2025-03-31 05:18:12 Duration: 1s27ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
10 54ms 2s741ms 782ms 13 10s176ms copy ( select array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ?) as broker_ids, string_to_array(coalesce(replace(broker_symbol_mappings, ?, ?), ?), ?) as broker_symbol_mappings, replace(exchange, ?, ?) as exchange, symbol_id, replace(symbol, ?, ?) as symbol, replace(short_name, ?, ?) as short_name, replace(long_name, ?, ?) as long_name, interval, replace(timezone, ?, ?) as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ?) as search_groups, string_to_array(pattern_basegroupnames, ?) as base_groups, simulation, signal_levels_entry_level, signal_levels_stop_level, signal_levels_target_level, signal_levels_target_period, signal_levels_filtered from solr_fetch_results (?::character varying, current_timestamp::timestamp without time zone)) t) to ?;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Mar 31 05 13 10s176ms 782ms [ User: postgres - Total duration: 10s176ms - Times executed: 13 ]
[ Application: psql - Total duration: 10s176ms - Times executed: 13 ]
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COPY ( select /*_solr_fetch_results__*/ array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ',') as broker_ids, string_to_array(COALESCE(replace(broker_symbol_mappings, '"', ''), ''), ',') as broker_symbol_mappings, replace(exchange, '"', '') as exchange,symbol_id,replace(symbol,'"','') as symbol, replace(short_name, '"', '') as short_name,replace(long_name,'"','') as long_name, interval, replace(timezone, '"', '') as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ',') as search_groups, string_to_array(pattern_basegroupnames, ',') as base_groups, simulation, signal_levels_entry_level, signal_levels_stop_level, signal_levels_target_level, signal_levels_target_period, signal_levels_filtered from solr_fetch_results ('Autochartist'::character varying, current_timestamp::timestamp without time zone)) t) TO '/tmp/solr_inserts_acaweb_fx.json';
Date: 2025-03-31 05:18:05 Duration: 2s741ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: psql
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COPY ( select /*_solr_fetch_results__*/ array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ',') as broker_ids, string_to_array(COALESCE(replace(broker_symbol_mappings, '"', ''), ''), ',') as broker_symbol_mappings, replace(exchange, '"', '') as exchange,symbol_id,replace(symbol,'"','') as symbol, replace(short_name, '"', '') as short_name,replace(long_name,'"','') as long_name, interval, replace(timezone, '"', '') as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ',') as search_groups, string_to_array(pattern_basegroupnames, ',') as base_groups, simulation, signal_levels_entry_level, signal_levels_stop_level, signal_levels_target_level, signal_levels_target_period, signal_levels_filtered from solr_fetch_results ('Autochartist'::character varying, current_timestamp::timestamp without time zone)) t) TO '/tmp/solr_inserts_acaweb_fx.json';
Date: 2025-03-31 05:33:04 Duration: 2s733ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: psql
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COPY ( select /*_solr_fetch_results__*/ array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ',') as broker_ids, string_to_array(COALESCE(replace(broker_symbol_mappings, '"', ''), ''), ',') as broker_symbol_mappings, replace(exchange, '"', '') as exchange,symbol_id,replace(symbol,'"','') as symbol, replace(short_name, '"', '') as short_name,replace(long_name,'"','') as long_name, interval, replace(timezone, '"', '') as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ',') as search_groups, string_to_array(pattern_basegroupnames, ',') as base_groups, simulation, signal_levels_entry_level, signal_levels_stop_level, signal_levels_target_level, signal_levels_target_period, signal_levels_filtered from solr_fetch_results ('Autochartist'::character varying, current_timestamp::timestamp without time zone)) t) TO '/tmp/solr_inserts_acaweb_fx.json';
Date: 2025-03-31 05:48:05 Duration: 2s340ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: psql
11 40ms 7s418ms 676ms 13 8s790ms copy ( select array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ?) as broker_ids, string_to_array(coalesce(replace(broker_symbol_mappings, ?, ?), ?), ?) as broker_symbol_mappings, replace(exchange, ?, ?) as exchange, symbol_id, replace(symbol, ?, ?) as symbol, replace(short_name, ?, ?) as short_name, replace(long_name, ?, ?) as long_name, interval, replace(timezone, ?, ?) as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ?) as search_groups, string_to_array(pattern_basegroupnames, ?) as base_groups, simulation from solr_fetch_results_bm_and_cc (?::character varying, current_timestamp::timestamp without time zone)) t) to ?;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Mar 31 05 13 8s790ms 676ms [ User: postgres - Total duration: 8s790ms - Times executed: 13 ]
[ Application: psql - Total duration: 8s790ms - Times executed: 13 ]
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COPY ( select /*_solr_fetch_results_bm_and_cc_*/ array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ',') as broker_ids, string_to_array(COALESCE(replace(broker_symbol_mappings, '"', ''), ''), ',') as broker_symbol_mappings, replace(exchange, '"', '') as exchange,symbol_id,replace(symbol,'"','') as symbol, replace(short_name, '"', '') as short_name,replace(long_name,'"','') as long_name, interval, replace(timezone, '"', '') as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ',') as search_groups, string_to_array(pattern_basegroupnames, ',') as base_groups, simulation from solr_fetch_results_bm_and_cc ('Autochartist'::character varying, current_timestamp::timestamp without time zone)) t) TO '/tmp/solr_inserts_bm_and_cc_acaweb_fx.json';
Date: 2025-03-31 05:03:09 Duration: 7s418ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: psql
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COPY ( select /*_solr_fetch_results_bm_and_cc_*/ array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ',') as broker_ids, string_to_array(COALESCE(replace(broker_symbol_mappings, '"', ''), ''), ',') as broker_symbol_mappings, replace(exchange, '"', '') as exchange,symbol_id,replace(symbol,'"','') as symbol, replace(short_name, '"', '') as short_name,replace(long_name,'"','') as long_name, interval, replace(timezone, '"', '') as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ',') as search_groups, string_to_array(pattern_basegroupnames, ',') as base_groups, simulation from solr_fetch_results_bm_and_cc ('Autochartist'::character varying, current_timestamp::timestamp without time zone)) t) TO '/tmp/solr_inserts_bm_and_cc_acaweb_fx.json';
Date: 2025-03-31 05:16:02 Duration: 379ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: psql
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COPY ( select /*_solr_fetch_results_bm_and_cc_*/ array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ',') as broker_ids, string_to_array(COALESCE(replace(broker_symbol_mappings, '"', ''), ''), ',') as broker_symbol_mappings, replace(exchange, '"', '') as exchange,symbol_id,replace(symbol,'"','') as symbol, replace(short_name, '"', '') as short_name,replace(long_name,'"','') as long_name, interval, replace(timezone, '"', '') as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ',') as search_groups, string_to_array(pattern_basegroupnames, ',') as base_groups, simulation from solr_fetch_results_bm_and_cc ('Autochartist'::character varying, current_timestamp::timestamp without time zone)) t) TO '/tmp/solr_inserts_bm_and_cc_acaweb_fx.json';
Date: 2025-03-31 05:11:02 Duration: 289ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: psql
12 147ms 1s678ms 560ms 231 2m9s with rar_max as ( select resultuid from relevance_consecutivecandles_results order by resultuid desc limit ? ), all_results as ( select ccr.resultuid as resultuid, ccr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ccr.patternendtime as identified, dtt.timezone as timezone, ccr.qtyconsecutivecandles as length, g.basegroupname, case when rcr.age is not null then rcr.age when ccr.resultuid <= rm.resultuid then ? else ? end as age, case when rcr.relevant is not null then rcr.relevant when ccr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip, newlevels.filtered from consecutivecandles_results ccr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = ccr.symbolid inner join symbols s on ccr.symbolid = s.symbolid and s.nonliquid = ? inner join downloadersymbolsettings dss on ccr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on ccr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join rar_max rm on ? = ? left outer join relevance_consecutivecandles_results rcr on rcr.resultuid = ccr.resultuid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? left join lateral calc_cc_signal_filter (ccr.resultuid) newlevels on true where ccr.gmttimefound > now() - interval ? and s.deleted = ? and (ccr.simulation = ? or ccr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ccr.patternlengthbars <= ?) ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Mar 31 05 231 2m9s 560ms [ User: postgres - Total duration: 2m9s - Times executed: 231 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m52s - Times executed: 219 ]
[ Application: [unknown] - Total duration: 17s31ms - Times executed: 12 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_consecutivecandles_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT ccr.resultuid AS resultuid, ccr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ccr.patternendtime AS identified, dtt.timezone AS timezone, ccr.qtyconsecutivecandles AS length, g.basegroupname, CASE WHEN rcr.age IS NOT NULL THEN rcr.age WHEN ccr.resultuid <= rm.resultuid THEN 1 ELSE 0 END as age, CASE WHEN rcr.relevant IS NOT NULL THEN rcr.relevant WHEN ccr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip, newLevels.filtered FROM consecutivecandles_results ccr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = ccr.symbolid INNER JOIN symbols s ON ccr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON ccr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on ccr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_consecutivecandles_results rcr ON rcr.resultuid = ccr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' LEFT JOIN LATERAL calc_cc_signal_filter (ccr.resultuid) newLevels on true WHERE ccr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('400' = 0 OR ccr.patternlengthbars <= '400') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-03-31 05:26:18 Duration: 1s678ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_consecutivecandles_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT ccr.resultuid AS resultuid, ccr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ccr.patternendtime AS identified, dtt.timezone AS timezone, ccr.qtyconsecutivecandles AS length, g.basegroupname, CASE WHEN rcr.age IS NOT NULL THEN rcr.age WHEN ccr.resultuid <= rm.resultuid THEN 1 ELSE 0 END as age, CASE WHEN rcr.relevant IS NOT NULL THEN rcr.relevant WHEN ccr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip, newLevels.filtered FROM consecutivecandles_results ccr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = ccr.symbolid INNER JOIN symbols s ON ccr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON ccr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on ccr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_consecutivecandles_results rcr ON rcr.resultuid = ccr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' LEFT JOIN LATERAL calc_cc_signal_filter (ccr.resultuid) newLevels on true WHERE ccr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('400' = 0 OR ccr.patternlengthbars <= '400') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-03-31 05:56:17 Duration: 1s633ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_consecutivecandles_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT ccr.resultuid AS resultuid, ccr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ccr.patternendtime AS identified, dtt.timezone AS timezone, ccr.qtyconsecutivecandles AS length, g.basegroupname, CASE WHEN rcr.age IS NOT NULL THEN rcr.age WHEN ccr.resultuid <= rm.resultuid THEN 1 ELSE 0 END as age, CASE WHEN rcr.relevant IS NOT NULL THEN rcr.relevant WHEN ccr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip, newLevels.filtered FROM consecutivecandles_results ccr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = ccr.symbolid INNER JOIN symbols s ON ccr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON ccr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on ccr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_consecutivecandles_results rcr ON rcr.resultuid = ccr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' LEFT JOIN LATERAL calc_cc_signal_filter (ccr.resultuid) newLevels on true WHERE ccr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('400' = 0 OR ccr.patternlengthbars <= '400') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-03-31 05:16:19 Duration: 1s628ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
13 85ms 904ms 353ms 135 47s750ms with last_candle as ( select acs.symbolid as symbolid, acs.latestpricedatetime as latest_candle_time, bsl.brokerid as broker_id, coalesce(bim.code, s.symbol) as symbol, bim.code as symbol_mapping, s.exchange as exchange, s.timegranularity as timegranularity from autochartist_symbolupdates acs inner join brokersymbollist bsl on acs.symbolid = bsl.symbolid inner join symbols s on acs.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where bsl.brokerid = ? and s.deleted = ? and s.nonliquid = ? and acs.latestpricedatetime is not null ) select * from ( select lc.broker_id as brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / ?) + ? as sast_hh, mod(cast(psp.fromtime as int), ?) as sast_mm, current_timestamp as datetime, (powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice as closingprice, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / ?.?) as low_15, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / ?.?) as high_15, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / ?.?) as low_30, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / ?.?) as high_30, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / ?.?) as low_60, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / ?.?) as high_60, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / ?.?) as low_240, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / ?.?) as high_240, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / ?.?) as low_1440, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / ?.?) as high_1440, dtt.absolutetimezoneoffset as datafeedtimezoneoffset, dtt.timezone as datafeedtimezonename, (round((cast(? as float) - rank) / ? * ?)) as rank_rounded, ((cast(? as float) - rank) / ? * ?) as rank from last_candle lc inner join downloadersymbolsettings dss on lc.symbolid = dss.symbolid inner join datafeedstimetable dtt on trim(dss.classname) = trim(dtt.classname) and dtt.dayofweek = ? -- assuming timezone is same for whole week. inner join powerstats_symboldata psd on psd.symbolid = lc.symbolid left outer join powerstats_trumpet psp on psd.trumpetsymbolid = psp.symbolid and psp.dayofweek = extract(dow from lc.latest_candle_time) and psp.fromtime = cast(extract(? from lc.latest_candle_time) as integer) * ? + extract(? from (cast(extract(? from lc.latest_candle_time) as integer) / ?) * ? * interval ?) inner join prfsymboltree prf on psd.symbolid = prf.symbolid and date_trunc(?, prf.enddate) = date_trunc(?, psp.enddate) left join lateral ( select ph.hour, (ave + stddev) as volatility, rank() over (order by (ave + stddev) desc) as rank from powerstats_hourly ph where ph.symbolid = psd.hourlysymbolid and date_trunc(?,ph.enddate) = date_trunc(?, prf.enddate) ) rank_query on true where prf.brokerid = ? and rank_query.hour = floor((psp.fromtime) / ?) and volatility > ? order by rank desc, rank_rounded desc, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Mar 31 05 135 47s750ms 353ms [ User: postgres - Total duration: 47s750ms - Times executed: 135 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 47s750ms - Times executed: 135 ]
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WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '529' AND s.deleted = 0 AND s.nonliquid = 0 AND acs.latestpricedatetime IS NOT NULL ) SELECT * FROM ( SELECT lc.broker_id AS brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / 60) + 6 as SAST_HH, mod(cast(psp.fromtime as int), 60) as SAST_MM, current_timestamp AS datetime, (PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice AS closingprice, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / 2.0) AS low_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / 2.0) AS high_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / 2.0) AS low_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / 2.0) AS high_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / 2.0) AS low_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / 2.0) AS high_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / 2.0) AS low_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / 2.0) AS high_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / 2.0) AS low_1440, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / 2.0) AS high_1440, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, (round((cast(25 as float) - rank) / 24 * 10)) as rank_rounded, ((cast(25 as float) - rank) / 24 * 10) as rank FROM last_candle lc INNER JOIN downloadersymbolsettings dss ON lc.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON TRIM(dss.classname) = TRIM(dtt.classname) and dtt.dayofweek = 3 -- assuming timezone is same for whole week. INNER JOIN powerstats_symboldata psd ON psd.symbolid = lc.symbolid LEFT OUTER JOIN powerstats_trumpet psp ON psd.trumpetsymbolid = psp.symbolid AND psp.dayofweek = extract(dow from lc.latest_candle_time) AND psp.fromtime = cast(extract('hour' from lc.latest_candle_time) as integer) * 60 + extract('minute' from (cast(extract('minute' from lc.latest_candle_time) as integer) / 15) * 15 * interval '1 minutes') INNER JOIN prfsymboltree prf ON psd.symbolid = prf.symbolid and DATE_TRUNC('day', prf.enddate) = DATE_TRUNC('day', psp.enddate) LEFT JOIN LATERAL ( SELECT ph.hour, (ave + stddev) AS volatility, rank() over (ORDER BY (ave + stddev) DESC) AS rank FROM powerstats_hourly ph WHERE ph.symbolid = psd.hourlysymbolid AND DATE_TRUNC('day', ph.enddate) = DATE_TRUNC('day', prf.enddate)) rank_query ON true WHERE prf.brokerid = '529' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2025-03-31 05:16:00 Duration: 904ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '529' AND s.deleted = 0 AND s.nonliquid = 0 AND acs.latestpricedatetime IS NOT NULL ) SELECT * FROM ( SELECT lc.broker_id AS brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / 60) + 6 as SAST_HH, mod(cast(psp.fromtime as int), 60) as SAST_MM, current_timestamp AS datetime, (PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice AS closingprice, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / 2.0) AS low_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / 2.0) AS high_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / 2.0) AS low_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / 2.0) AS high_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / 2.0) AS low_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / 2.0) AS high_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / 2.0) AS low_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / 2.0) AS high_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / 2.0) AS low_1440, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / 2.0) AS high_1440, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, (round((cast(25 as float) - rank) / 24 * 10)) as rank_rounded, ((cast(25 as float) - rank) / 24 * 10) as rank FROM last_candle lc INNER JOIN downloadersymbolsettings dss ON lc.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON TRIM(dss.classname) = TRIM(dtt.classname) and dtt.dayofweek = 3 -- assuming timezone is same for whole week. INNER JOIN powerstats_symboldata psd ON psd.symbolid = lc.symbolid LEFT OUTER JOIN powerstats_trumpet psp ON psd.trumpetsymbolid = psp.symbolid AND psp.dayofweek = extract(dow from lc.latest_candle_time) AND psp.fromtime = cast(extract('hour' from lc.latest_candle_time) as integer) * 60 + extract('minute' from (cast(extract('minute' from lc.latest_candle_time) as integer) / 15) * 15 * interval '1 minutes') INNER JOIN prfsymboltree prf ON psd.symbolid = prf.symbolid and DATE_TRUNC('day', prf.enddate) = DATE_TRUNC('day', psp.enddate) LEFT JOIN LATERAL ( SELECT ph.hour, (ave + stddev) AS volatility, rank() over (ORDER BY (ave + stddev) DESC) AS rank FROM powerstats_hourly ph WHERE ph.symbolid = psd.hourlysymbolid AND DATE_TRUNC('day', ph.enddate) = DATE_TRUNC('day', prf.enddate)) rank_query ON true WHERE prf.brokerid = '529' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2025-03-31 05:16:00 Duration: 877ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '529' AND s.deleted = 0 AND s.nonliquid = 0 AND acs.latestpricedatetime IS NOT NULL ) SELECT * FROM ( SELECT lc.broker_id AS brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / 60) + 6 as SAST_HH, mod(cast(psp.fromtime as int), 60) as SAST_MM, current_timestamp AS datetime, (PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice AS closingprice, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / 2.0) AS low_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / 2.0) AS high_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / 2.0) AS low_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / 2.0) AS high_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / 2.0) AS low_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / 2.0) AS high_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / 2.0) AS low_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / 2.0) AS high_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / 2.0) AS low_1440, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / 2.0) AS high_1440, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, (round((cast(25 as float) - rank) / 24 * 10)) as rank_rounded, ((cast(25 as float) - rank) / 24 * 10) as rank FROM last_candle lc INNER JOIN downloadersymbolsettings dss ON lc.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON TRIM(dss.classname) = TRIM(dtt.classname) and dtt.dayofweek = 3 -- assuming timezone is same for whole week. INNER JOIN powerstats_symboldata psd ON psd.symbolid = lc.symbolid LEFT OUTER JOIN powerstats_trumpet psp ON psd.trumpetsymbolid = psp.symbolid AND psp.dayofweek = extract(dow from lc.latest_candle_time) AND psp.fromtime = cast(extract('hour' from lc.latest_candle_time) as integer) * 60 + extract('minute' from (cast(extract('minute' from lc.latest_candle_time) as integer) / 15) * 15 * interval '1 minutes') INNER JOIN prfsymboltree prf ON psd.symbolid = prf.symbolid and DATE_TRUNC('day', prf.enddate) = DATE_TRUNC('day', psp.enddate) LEFT JOIN LATERAL ( SELECT ph.hour, (ave + stddev) AS volatility, rank() over (ORDER BY (ave + stddev) DESC) AS rank FROM powerstats_hourly ph WHERE ph.symbolid = psd.hourlysymbolid AND DATE_TRUNC('day', ph.enddate) = DATE_TRUNC('day', prf.enddate)) rank_query ON true WHERE prf.brokerid = '529' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2025-03-31 05:28:00 Duration: 846ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
14 12ms 3s907ms 350ms 34 11s902ms select fixcandlegaps (?, false);Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Mar 31 05 34 11s902ms 350ms [ User: postgres - Total duration: 11s902ms - Times executed: 34 ]
[ Application: psql - Total duration: 11s902ms - Times executed: 34 ]
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select fixcandlegaps ('ICMARKETS-AU-MT5', false);
Date: 2025-03-31 05:06:14 Duration: 3s907ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('ATFX', false);
Date: 2025-03-31 05:06:05 Duration: 1s258ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('PEPPERSTONE', false);
Date: 2025-03-31 05:06:08 Duration: 1s69ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
15 25ms 435ms 109ms 231 25s299ms with rar_max as ( select resultuid from relevance_bigmovement_results order by resultuid desc limit ? ), all_results as ( select bmr.resultuid as resultuid, ? 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, bmr.patternendtime as identified, bmr.patternlengthbars, dtt.timezone as timezone, g.basegroupname, 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 brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = bmr.symbolid inner join symbols s on bmr.symbolid = s.symbolid and s.nonliquid = ? inner join downloadersymbolsettings dss on bmr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on bmr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join rar_max rm on ? = ? left outer join relevance_bigmovement_results rbr on rbr.resultuid = bmr.resultuid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where bmr.gmttimefound > now() - interval ? and s.deleted = ? and (bmr.simulation = ? or bmr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or bmr.patternlengthbars <= ?) ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, interval desc;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Mar 31 05 231 25s299ms 109ms [ User: postgres - Total duration: 25s299ms - Times executed: 231 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 21s133ms - Times executed: 219 ]
[ Application: [unknown] - Total duration: 4s165ms - Times executed: 12 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_bigmovement_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT bmr.resultuid AS resultuid, 0 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, bmr.patternendtime AS identified, bmr.patternlengthbars, dtt.timezone AS timezone, g.basegroupname, CASE WHEN rbr.age IS NOT NULL THEN rbr.age WHEN bmr.resultuid <= rm.resultuid THEN 4 ELSE 0 END as age, CASE WHEN rbr.relevant IS NOT NULL THEN rbr.relevant WHEN bmr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM bigmovement_results bmr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = bmr.symbolid INNER JOIN symbols s ON bmr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON bmr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on bmr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_bigmovement_results rbr ON rbr.resultuid = bmr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bmr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (bmr.simulation = 0 OR bmr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('400' = 0 OR bmr.patternlengthbars <= '400') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, interval DESC;
Date: 2025-03-31 05:31:14 Duration: 435ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_bigmovement_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT bmr.resultuid AS resultuid, 0 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, bmr.patternendtime AS identified, bmr.patternlengthbars, dtt.timezone AS timezone, g.basegroupname, CASE WHEN rbr.age IS NOT NULL THEN rbr.age WHEN bmr.resultuid <= rm.resultuid THEN 4 ELSE 0 END as age, CASE WHEN rbr.relevant IS NOT NULL THEN rbr.relevant WHEN bmr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM bigmovement_results bmr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = bmr.symbolid INNER JOIN symbols s ON bmr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON bmr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on bmr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_bigmovement_results rbr ON rbr.resultuid = bmr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bmr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (bmr.simulation = 0 OR bmr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('400' = 0 OR bmr.patternlengthbars <= '400') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, interval DESC;
Date: 2025-03-31 05:16:20 Duration: 419ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_bigmovement_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT bmr.resultuid AS resultuid, 0 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, bmr.patternendtime AS identified, bmr.patternlengthbars, dtt.timezone AS timezone, g.basegroupname, CASE WHEN rbr.age IS NOT NULL THEN rbr.age WHEN bmr.resultuid <= rm.resultuid THEN 4 ELSE 0 END as age, CASE WHEN rbr.relevant IS NOT NULL THEN rbr.relevant WHEN bmr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM bigmovement_results bmr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = bmr.symbolid INNER JOIN symbols s ON bmr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON bmr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on bmr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_bigmovement_results rbr ON rbr.resultuid = bmr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bmr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (bmr.simulation = 0 OR bmr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('400' = 0 OR bmr.patternlengthbars <= '400') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, interval DESC;
Date: 2025-03-31 05:51:17 Duration: 413ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
16 15ms 367ms 74ms 177 13s233ms select distinct k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid from relevance_keylevels_results p inner join keylevels_results k on p.resultuid = k.resultuid inner join autochartist_stocklist asl on k.symbolid = asl.symbolid where k.patternclassid in (...) and asl.enabled = ? and asl.recognitionengine ilike ?;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Mar 31 05 177 13s233ms 74ms [ User: postgres - Total duration: 13s233ms - Times executed: 177 ]
[ Application: [unknown] - Total duration: 13s233ms - Times executed: 177 ]
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SELECT DISTINCT k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid FROM relevance_keylevels_results p INNER JOIN keylevels_results k ON p.resultuid = k.resultuid INNER JOIN autochartist_stocklist asl ON k.symbolid = asl.symbolid WHERE k.patternclassid in (1, 2) AND asl.enabled = 1 AND asl.recognitionengine ILIKE 'ATFX - 1';
Date: 2025-03-31 05:31:01 Duration: 367ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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SELECT DISTINCT k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid FROM relevance_keylevels_results p INNER JOIN keylevels_results k ON p.resultuid = k.resultuid INNER JOIN autochartist_stocklist asl ON k.symbolid = asl.symbolid WHERE k.patternclassid in (1, 2) AND asl.enabled = 1 AND asl.recognitionengine ILIKE 'ICMARKETS - 1';
Date: 2025-03-31 05:16:00 Duration: 260ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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SELECT DISTINCT k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid FROM relevance_keylevels_results p INNER JOIN keylevels_results k ON p.resultuid = k.resultuid INNER JOIN autochartist_stocklist asl ON k.symbolid = asl.symbolid WHERE k.patternclassid in (1, 2) AND asl.enabled = 1 AND asl.recognitionengine ILIKE 'ATFX - 1';
Date: 2025-03-31 05:06:18 Duration: 242ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
17 0ms 254ms 58ms 336 19s500ms select distinct a.resultuid as ruid, c.symbolid as sid, c.symbol as sym, c.longname as longname, c.shortname, c.exchange as e, c.timegranularity as tg, p.patternid as pid, a.direction as d, cast(atbaridentified as timestamp) as pet, cast(patternstarttime as timestamp) as pst, patternprice as patp, breakoutprice as pe, breakoutbars as be, errormargin as erm, patternlengthbars as l, bandwidth as bw, qtytp as qtp, p.patternname as patternname, cast(x0 as timestamp) as x0, cast(x1 as timestamp) as x1, cast(x2 as timestamp) as x2, cast(( case when x3 = ? then ? else x3 end) as timestamp) as x3, cast(( case when x4 = ? then ? else x4 end) as timestamp) as x4, cast(( case when x5 = ? then ? else x5 end) as timestamp) as x5, cast(( case when x6 = ? then ? else x6 end) as timestamp) as x6, cast(( case when x7 = ? then ? else x7 end) as timestamp) as x7, cast(( case when x8 = ? then ? else x8 end) as timestamp) as x8, cast(( case when x9 = ? then ? else x9 end) as timestamp) as x9, cast(atbaridentified as timestamp) as patternendtime, cast(atbaridentified as timestamp) as atbar, cast(( case when approachingtimestamp = ? then ? else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzos, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, case when rar.age is not null then rar.age when a.resultuid <= ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) then ? else ? end as relevant, cast(?.? as double precision) as premium, cast(? as bigint) as instrumentid, ? as derivativeid, ? as underlyingid, ? as isunderlying from symbols c inner join brokersymbollist b on c.symbolid = b.symbolid inner join symbolgroup sg on c.symbolid = sg.symbolid inner join downloadersymbolsettings dss on dss.symbolid = c.symbolid inner join datafeedstimetable dftt on dftt.classname = dss.classname inner join keylevels_results a on a.symbolid = c.symbolid inner join hrspatterns p on a.patternid = p.patternid left outer join relevance_keylevels_results rar on rar.resultuid = a.resultuid where b.brokerid = ? and sg.groupid = ? and patternclassid = ? and patternlengthbars >= ? and a.patternid & ? > ? and dftt.dayofweek = ? and a.qtytp >= ? and a.resultuid > ? and c.nonliquid = ? and c.deleted = ? and dss.enabled = ? order by relevant desc, age asc, patternendtime desc, qtp desc limit ?;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Mar 31 05 336 19s500ms 58ms [ User: postgres - Total duration: 19s500ms - Times executed: 336 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 19s500ms - Times executed: 336 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059758978308 AND patternclassid = '2' AND patternlengthbars >= '20' AND a.PatternID & '39' > 0 AND dftt.dayofweek = '3' AND a.qtytp >= '0' AND a.resultuid > '-919550705' AND c.nonliquid = '0' AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:16:05 Duration: 254ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059718346308 AND patternclassid = '2' AND patternlengthbars >= '20' AND a.PatternID & '39' > 0 AND dftt.dayofweek = '3' AND a.qtytp >= '0' AND a.resultuid > '-628120145' AND c.nonliquid = '0' AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:32:06 Duration: 252ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059718346308 AND patternclassid = '2' AND patternlengthbars >= '20' AND a.PatternID & '39' > 0 AND dftt.dayofweek = '3' AND a.qtytp >= '0' AND a.resultuid > '-628120145' AND c.nonliquid = '0' AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:16:05 Duration: 248ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
18 15ms 166ms 44ms 177 7s812ms select distinct a.symbolid, p.resultuid, case when a.breakout >= ? then ? else ? end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient from relevance_autochartist_results p inner join autochartist_results a on p.resultuid = a.resultuid inner join autochartist_stocklist asl on a.symbolid = asl.symbolid where asl.enabled = ? and asl.recognitionengine ilike ?;Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Mar 31 05 177 7s812ms 44ms [ User: postgres - Total duration: 7s812ms - Times executed: 177 ]
[ Application: [unknown] - Total duration: 7s812ms - Times executed: 177 ]
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SELECT distinct a.symbolid, p.resultuid, case when a.breakout >= 0 then 1 else 2 end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient FROM relevance_autochartist_results p INNER JOIN autochartist_results a ON p.resultuid = a.resultuid INNER JOIN autochartist_stocklist asl ON a.symbolid = asl.symbolid WHERE asl.enabled = 1 AND asl.recognitionengine ILIKE 'ICMARKETS - 1';
Date: 2025-03-31 05:16:00 Duration: 166ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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SELECT distinct a.symbolid, p.resultuid, case when a.breakout >= 0 then 1 else 2 end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient FROM relevance_autochartist_results p INNER JOIN autochartist_results a ON p.resultuid = a.resultuid INNER JOIN autochartist_stocklist asl ON a.symbolid = asl.symbolid WHERE asl.enabled = 1 AND asl.recognitionengine ILIKE 'ICMARKETS - 1';
Date: 2025-03-31 05:45:57 Duration: 165ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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SELECT distinct a.symbolid, p.resultuid, case when a.breakout >= 0 then 1 else 2 end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient FROM relevance_autochartist_results p INNER JOIN autochartist_results a ON p.resultuid = a.resultuid INNER JOIN autochartist_stocklist asl ON a.symbolid = asl.symbolid WHERE asl.enabled = 1 AND asl.recognitionengine ILIKE 'ICMARKETS - 1';
Date: 2025-03-31 05:17:09 Duration: 165ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
19 0ms 22ms 2ms 15,112 33s946ms 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 #19
Day Hour Count Duration Avg duration Mar 31 05 15,112 33s946ms 2ms [ User: postgres - Total duration: 33s946ms - Times executed: 15112 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 33s946ms - Times executed: 15112 ]
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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 = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '558' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'EURAUD' OR dss.downloadersymbol = 'EURAUD') AND dss.enabled = 1;
Date: 2025-03-31 05:00:04 Duration: 22ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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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 = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '558' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'AUDCAD' OR dss.downloadersymbol = 'AUDCAD') AND dss.enabled = 1;
Date: 2025-03-31 05:00:03 Duration: 20ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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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 = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'NZDCHF' OR dss.downloadersymbol = 'NZDCHF') AND dss.enabled = 1;
Date: 2025-03-31 05:30:06 Duration: 19ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
20 0ms 13ms 2ms 1,561 3s382ms select * from ( select pricedatetime as datetime, open as open, high as high, low as low, close "..." close, volume as volume from t240 where symbolid = ? order by pricedatetime desc limit ?) as tmp order by datetime asc;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Mar 31 05 1,561 3s382ms 2ms [ User: postgres - Total duration: 3s382ms - Times executed: 1561 ]
[ Application: [unknown] - Total duration: 3s382ms - Times executed: 1561 ]
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select * from ( select pricedatetime as DateTime, open as Open, high as High, low as Low, close as Close, volume as Volume from T240 where symbolid = 500991628282619200 order by pricedatetime desc limit 600) as tmp order by datetime asc;
Date: 2025-03-31 05:30:05 Duration: 13ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown] Bind query: yes
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select * from ( select pricedatetime as DateTime, open as Open, high as High, low as Low, close as Close, volume as Volume from T240 where symbolid = 500991628280178200 order by pricedatetime desc limit 600) as tmp order by datetime asc;
Date: 2025-03-31 05:30:05 Duration: 12ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown] Bind query: yes
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select * from ( select pricedatetime as DateTime, open as Open, high as High, low as Low, close as Close, volume as Volume from T240 where symbolid = 515840216970544300 order by pricedatetime desc limit 600) as tmp order by datetime asc;
Date: 2025-03-31 05:30:05 Duration: 10ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown] Bind query: yes
Time consuming prepare
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 1s644ms 2,001 0ms 5ms 0ms WITH rar_max as ( ;Times Reported Time consuming prepare #1
Day Hour Count Duration Avg duration Mar 31 05 2,001 1s644ms 0ms [ User: postgres - Total duration: 1h38m1s - Times executed: 2001 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1h33m8s - Times executed: 1962 ]
[ Application: [unknown] - Total duration: 4m52s - Times executed: 39 ]
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WITH rar_max as ( ;
Date: 2025-03-31 05:01:18 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
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WITH rar_max as ( ;
Date: 2025-03-31 05:17:18 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
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WITH rar_max as ( ;
Date: 2025-03-31 05:18:08 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
2 787ms 2,575 0ms 6ms 0ms SELECT ;Times Reported Time consuming prepare #2
Day Hour Count Duration Avg duration 05 2,575 787ms 0ms [ User: postgres - Total duration: 3s346ms - Times executed: 2575 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 3s112ms - Times executed: 1872 ]
[ Application: [unknown] - Total duration: 234ms - Times executed: 703 ]
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SELECT ;
Date: 2025-03-31 05:30:04 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
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SELECT ;
Date: 2025-03-31 05:30:04 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
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SELECT ;
Date: 2025-03-31 05:00:04 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
3 782ms 567 0ms 5ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming prepare #3
Day Hour Count Duration Avg duration 05 567 782ms 1ms [ User: postgres - Total duration: 957ms - Times executed: 567 ]
[ Application: [unknown] - Total duration: 957ms - Times executed: 567 ]
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-03-31 05:31:03 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-03-31 05:31:00 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-03-31 05:31:03 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
4 524ms 1,580 0ms 2ms 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 #4
Day Hour Count Duration Avg duration 05 1,580 524ms 0ms [ User: postgres - Total duration: 4s501ms - Times executed: 1580 ]
[ Application: [unknown] - Total duration: 4s501ms - Times executed: 1580 ]
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INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-03-31 05:30:06 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-03-31 05:30:53 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-03-31 05:16:00 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
5 292ms 3,222 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 #5
Day Hour Count Duration Avg duration 05 3,222 292ms 0ms [ User: postgres - Total duration: 1s749ms - Times executed: 3222 ]
[ Application: [unknown] - Total duration: 1s749ms - Times executed: 3222 ]
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INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-03-31 05:30:59 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-03-31 05:00:46 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-03-31 05:00:42 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
6 221ms 2,143 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 #6
Day Hour Count Duration Avg duration 05 2,143 221ms 0ms [ User: postgres - Total duration: 972ms - Times executed: 2143 ]
[ Application: [unknown] - Total duration: 972ms - Times executed: 2143 ]
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-03-31 05:01:01 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-03-31 05:00:53 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-03-31 05:00:42 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
7 158ms 5,021 0ms 0ms 0ms insert into sa_hist_consecutivecandles (symbolid, datetime, image, qty, percentile, direction, height) values ($1, $2, $3, $4, $5, $6, $7);Times Reported Time consuming prepare #7
Day Hour Count Duration Avg duration 05 5,021 158ms 0ms [ User: postgres - Total duration: 189ms - Times executed: 5021 ]
[ Application: [unknown] - Total duration: 189ms - Times executed: 5021 ]
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insert into sa_hist_consecutivecandles (symbolid, datetime, image, qty, percentile, direction, height) values ($1, $2, $3, $4, $5, $6, $7);
Date: 2025-03-31 05:30:04 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 127.0.0.1
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insert into sa_hist_consecutivecandles (symbolid, datetime, image, qty, percentile, direction, height) values ($1, $2, $3, $4, $5, $6, $7);
Date: 2025-03-31 05:30:06 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 127.0.0.1
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insert into sa_hist_consecutivecandles (symbolid, datetime, image, qty, percentile, direction, height) values ($1, $2, $3, $4, $5, $6, $7);
Date: 2025-03-31 05:30:11 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 127.0.0.1
8 143ms 1,030 0ms 4ms 0ms SET extra_float_digits = 3;Times Reported Time consuming prepare #8
Day Hour Count Duration Avg duration 05 1,030 143ms 0ms [ User: postgres - Total duration: 9ms - Times executed: 1030 ]
[ Application: [unknown] - Total duration: 9ms - Times executed: 1030 ]
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SET extra_float_digits = 3;
Date: 2025-03-31 05:28:04 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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SET extra_float_digits = 3;
Date: 2025-03-31 05:04:04 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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SET extra_float_digits = 3;
Date: 2025-03-31 05:20:04 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
9 127ms 1,893 0ms 2ms 0ms select 1;Times Reported Time consuming prepare #9
Day Hour Count Duration Avg duration 05 1,893 127ms 0ms [ User: postgres - Total duration: 8ms - Times executed: 1893 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 7ms - Times executed: 1881 ]
[ Application: [unknown] - Total duration: 0ms - Times executed: 12 ]
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select 1;
Date: 2025-03-31 05:20:05 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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select 1;
Date: 2025-03-31 05:04:04 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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select 1;
Date: 2025-03-31 05:40:04 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
10 91ms 16 4ms 7ms 5ms with sym_info as ( ;Times Reported Time consuming prepare #10
Day Hour Count Duration Avg duration 05 16 91ms 5ms [ User: postgres - Total duration: 21s556ms - Times executed: 16 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 21s556ms - Times executed: 16 ]
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with sym_info as ( ;
Date: 2025-03-31 05:51:44 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
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with sym_info as ( ;
Date: 2025-03-31 05:06:42 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
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with sym_info as ( ;
Date: 2025-03-31 05:51:56 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
11 91ms 28 2ms 3ms 3ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059725121308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming prepare #11
Day Hour Count Duration Avg duration 05 28 91ms 3ms [ User: postgres - Total duration: 12ms - Times executed: 28 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 12ms - Times executed: 28 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059725121308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:48:04 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059725121308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:40:04 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059725121308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:00:03 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
12 70ms 28 0ms 6ms 2ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059710817308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.resultuid > $5 AND c.nonliquid = $6 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming prepare #12
Day Hour Count Duration Avg duration 05 28 70ms 2ms [ User: postgres - Total duration: 281ms - Times executed: 28 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 281ms - Times executed: 28 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059710817308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.resultuid > $5 AND c.nonliquid = $6 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:52:05 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059710817308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.resultuid > $5 AND c.nonliquid = $6 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:24:04 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059710817308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.resultuid > $5 AND c.nonliquid = $6 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:32:04 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
13 66ms 64 0ms 3ms 1ms WITH last_candle AS ( ;Times Reported Time consuming prepare #13
Day Hour Count Duration Avg duration 05 64 66ms 1ms [ User: postgres - Total duration: 26s518ms - Times executed: 64 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 26s518ms - Times executed: 64 ]
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WITH last_candle AS ( ;
Date: 2025-03-31 05:16:00 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
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WITH last_candle AS ( ;
Date: 2025-03-31 05:32:00 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
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WITH last_candle AS ( ;
Date: 2025-03-31 05:04:00 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
14 65ms 28 0ms 5ms 2ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059714438308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming prepare #14
Day Hour Count Duration Avg duration 05 28 65ms 2ms [ User: postgres - Total duration: 2s400ms - Times executed: 28 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2s400ms - Times executed: 28 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059714438308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:00:03 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059714438308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:00:03 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059714438308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:52:05 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
15 62ms 28 0ms 8ms 2ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059704165308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming prepare #15
Day Hour Count Duration Avg duration 05 28 62ms 2ms [ User: postgres - Total duration: 1s149ms - Times executed: 28 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s149ms - Times executed: 28 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059704165308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:08:04 Duration: 8ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059704165308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:32:05 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059704165308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:28:05 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
16 61ms 28 0ms 3ms 2ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059759428308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming prepare #16
Day Hour Count Duration Avg duration 05 28 61ms 2ms [ User: postgres - Total duration: 755ms - Times executed: 28 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 755ms - Times executed: 28 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059759428308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:16:04 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059759428308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:04:04 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059759428308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:04:04 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
17 56ms 14 0ms 14ms 4ms /*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059711596308 AND patternlengthbars >= 20 AND averagequality >= 0.0 AND (timequality >= 0.0 OR timequality = - 1) AND errormargin >= 0.0 AND 1 - noise >= 0.0 AND s.nonliquid = 0 AND PatternID & 39 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND PatternEndPrice = - 1 AND a.resultuid > 605863012040954302 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, averagequality DESC LIMIT 50;Times Reported Time consuming prepare #17
Day Hour Count Duration Avg duration 05 14 56ms 4ms [ User: postgres - Total duration: 25ms - Times executed: 14 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 25ms - Times executed: 14 ]
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059711596308 AND patternlengthbars >= 20 AND averagequality >= 0.0 AND (timequality >= 0.0 OR timequality = - 1) AND errormargin >= 0.0 AND 1 - noise >= 0.0 AND s.nonliquid = 0 AND PatternID & 39 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND PatternEndPrice = - 1 AND a.resultuid > 605863012040954302 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, averagequality DESC LIMIT 50;
Date: 2025-03-31 05:20:04 Duration: 14ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059711596308 AND patternlengthbars >= 20 AND averagequality >= 0.0 AND (timequality >= 0.0 OR timequality = - 1) AND errormargin >= 0.0 AND 1 - noise >= 0.0 AND s.nonliquid = 0 AND PatternID & 39 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND PatternEndPrice = - 1 AND a.resultuid > 605863012040954302 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, averagequality DESC LIMIT 50;
Date: 2025-03-31 05:52:05 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059711596308 AND patternlengthbars >= 20 AND averagequality >= 0.0 AND (timequality >= 0.0 OR timequality = - 1) AND errormargin >= 0.0 AND 1 - noise >= 0.0 AND s.nonliquid = 0 AND PatternID & 39 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND PatternEndPrice = - 1 AND a.resultuid > 605863012040954302 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, averagequality DESC LIMIT 50;
Date: 2025-03-31 05:24:04 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
18 54ms 28 0ms 3ms 1ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059711596308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming prepare #18
Day Hour Count Duration Avg duration 05 28 54ms 1ms [ User: postgres - Total duration: 674ms - Times executed: 28 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 674ms - Times executed: 28 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059711596308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:32:04 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059711596308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:24:04 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059711596308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:52:05 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
19 53ms 28 0ms 5ms 1ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059706590308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming prepare #19
Day Hour Count Duration Avg duration 05 28 53ms 1ms [ User: postgres - Total duration: 1s411ms - Times executed: 28 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s411ms - Times executed: 28 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059706590308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:00:03 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059706590308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:24:04 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059706590308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:48:05 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
20 52ms 28 0ms 3ms 1ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059720124308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming prepare #20
Day Hour Count Duration Avg duration 05 28 52ms 1ms [ User: postgres - Total duration: 546ms - Times executed: 28 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 546ms - Times executed: 28 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059720124308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:20:04 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059720124308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:12:04 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059720124308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:48:05 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
Time consuming bind
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 26s169ms 2,742 0ms 36ms 9ms WITH rar_max as ( ;Times Reported Time consuming bind #1
Day Hour Count Duration Avg duration Mar 31 05 2,742 26s169ms 9ms [ User: postgres - Total duration: 1h54m41s - Times executed: 2742 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1h46m4s - Times executed: 2672 ]
[ Application: [unknown] - Total duration: 8m36s - Times executed: 70 ]
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WITH rar_max as ( ;
Date: 2025-03-31 05:28:04 Duration: 36ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250 parameters: $1 = '605863128184174301', $2 = '605863128184174301', $3 = '605863128184174301'
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WITH rar_max as ( ;
Date: 2025-03-31 05:28:04 Duration: 35ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = 't', $2 = '667', $3 = '7', $4 = '15', $5 = '30', $6 = '60', $7 = '120', $8 = '240', $9 = '480', $10 = '1440', $11 = '0', $12 = '', $13 = '84', $14 = 'AUDCAD', $15 = 'AUDCHF', $16 = 'AUDJPY', $17 = 'AUDNZD', $18 = 'AUDSGD', $19 = 'CADCHF', $20 = 'CADJPY', $21 = 'CHFJPY', $22 = 'EURAUD', $23 = 'EURCAD', $24 = 'EURCHF', $25 = 'EURCZK', $26 = 'EURGBP', $27 = 'EURHUF', $28 = 'EURJPY', $29 = 'EURNOK', $30 = 'EURNZD', $31 = 'EURPLN', $32 = 'EURSEK', $33 = 'EURSGD', $34 = 'EURTRY', $35 = 'EURZAR', $36 = 'GBPAUD', $37 = 'GBPCAD', $38 = 'GBPCHF', $39 = 'GBPJPY', $40 = 'GBPNZD', $41 = 'GBPPLN', $42 = 'GBPSEK', $43 = 'GBPSGD', $44 = 'NZDCAD', $45 = 'NZDCHF', $46 = 'NZDJPY', $47 = 'NZDSGD', $48 = 'USDCNH', $49 = 'USDCZK', $50 = 'USDHUF', $51 = 'USDNOK', $52 = 'USDPLN', $53 = 'USDSEK', $54 = 'USDSGD', $55 = 'USDTRY', $56 = 'USDZAR', $57 = 'WTI', $58 = 'XBRUSD', $59 = 'XTIUSD', $60 = 'BTCUSD', $61 = 'XAGAUD', $62 = 'XAGUSD', $63 = 'XAUAUD', $64 = 'XAUUSD', $65 = 'XPTUSD', $66 = 'XPDUSD', $67 = 'AUDUSD', $68 = 'EURUSD', $69 = 'GBPUSD', $70 = 'NZDUSD', $71 = 'USDCAD', $72 = 'USDCHF', $73 = 'USDHKD', $74 = 'USDJPY', $75 = 'AUS200', $76 = 'CHINA300', $77 = 'CHINA50', $78 = 'DJ30', $79 = 'ESP35t', $80 = 'EUR50', $81 = 'EURO50', $82 = 'FRA40', $83 = 'GDAXI', $84 = 'GDAXIm', $85 = 'HK50', $86 = 'ITA40', $87 = 'J225', $88 = 'JP225', $89 = 'NAS100', $90 = 'SING30', $91 = 'SPA35', $92 = 'STOXX50', $93 = 'SUI20', $94 = 'UK100', $95 = 'US100', $96 = 'US30', $97 = 'US500', $98 = '0', $99 = '', $100 = '0', $101 = '0', $102 = '0', $103 = '400', $104 = '400', $105 = 't', $106 = '10', $107 = '10'
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WITH rar_max as ( ;
Date: 2025-03-31 05:31:01 Duration: 34ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250 parameters: $1 = 't', $2 = '667', $3 = '0', $4 = '0', $5 = '0', $6 = '', $7 = '0', $8 = '', $9 = '0', $10 = '', $11 = '0', $12 = '0', $13 = '0', $14 = '0', $15 = '0', $16 = 't', $17 = '0', $18 = '0'
2 13s597ms 35,109 0ms 25ms 0ms SELECT ;Times Reported Time consuming bind #2
Day Hour Count Duration Avg duration 05 35,109 13s597ms 0ms [ User: postgres - Total duration: 55s617ms - Times executed: 35109 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 55s380ms - Times executed: 34400 ]
[ Application: [unknown] - Total duration: 236ms - Times executed: 709 ]
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SELECT ;
Date: 2025-03-31 05:00:03 Duration: 25ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '558', $2 = '0', $3 = '0', $4 = 'EURZAR', $5 = 'EURZAR'
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SELECT ;
Date: 2025-03-31 05:00:03 Duration: 19ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '558', $2 = '0', $3 = '0', $4 = 'NZDCHF', $5 = 'NZDCHF'
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SELECT ;
Date: 2025-03-31 05:00:03 Duration: 16ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '558', $2 = '0', $3 = '0', $4 = 'XAGEUR', $5 = 'XAGEUR'
3 1s62ms 567 1ms 4ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming bind #3
Day Hour Count Duration Avg duration 05 567 1s62ms 1ms [ User: postgres - Total duration: 957ms - Times executed: 567 ]
[ Application: [unknown] - Total duration: 957ms - Times executed: 567 ]
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-03-31 05:31:03 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = 'ICMARKETS-AU-MT5'
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-03-31 05:31:03 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = 'BDSWISS'
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-03-31 05:46:05 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = 'FPMARKETS'
4 1s47ms 135 4ms 34ms 7ms WITH last_candle AS ( ;Times Reported Time consuming bind #4
Day Hour Count Duration Avg duration 05 135 1s47ms 7ms [ User: postgres - Total duration: 47s750ms - Times executed: 135 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 47s750ms - Times executed: 135 ]
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WITH last_candle AS ( ;
Date: 2025-03-31 05:00:02 Duration: 34ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '558', $2 = '558'
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WITH last_candle AS ( ;
Date: 2025-03-31 05:00:00 Duration: 17ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '529', $2 = '529'
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WITH last_candle AS ( ;
Date: 2025-03-31 05:16:00 Duration: 13ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '529', $2 = '529'
5 1s41ms 50 0ms 52ms 20ms with wh_patitioned as ( ;Times Reported Time consuming bind #5
Day Hour Count Duration Avg duration 05 50 1s41ms 20ms [ User: postgres - Total duration: 998ms - Times executed: 50 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 998ms - Times executed: 50 ]
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with wh_patitioned as ( ;
Date: 2025-03-31 05:28:59 Duration: 52ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
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with wh_patitioned as ( ;
Date: 2025-03-31 05:18:08 Duration: 48ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
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with wh_patitioned as ( ;
Date: 2025-03-31 05:27:08 Duration: 47ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
6 874ms 28 11ms 53ms 31ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059759428308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming bind #6
Day Hour Count Duration Avg duration 05 28 874ms 31ms [ User: postgres - Total duration: 755ms - Times executed: 28 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 755ms - Times executed: 28 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059759428308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:04:04 Duration: 53ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-1307241977', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059759428308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:08:04 Duration: 52ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-1307241977', $7 = '0'
-
/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059759428308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:20:04 Duration: 52ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-1307241977', $7 = '0'
7 847ms 28 10ms 61ms 30ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059704165308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming bind #7
Day Hour Count Duration Avg duration 05 28 847ms 30ms [ User: postgres - Total duration: 1s149ms - Times executed: 28 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s149ms - Times executed: 28 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059704165308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:04:04 Duration: 61ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '899406415', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059704165308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:04:04 Duration: 53ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-851282713', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059704165308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:08:04 Duration: 52ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '899406415', $7 = '0'
8 763ms 28 10ms 58ms 27ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059714438308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming bind #8
Day Hour Count Duration Avg duration 05 28 763ms 27ms [ User: postgres - Total duration: 2s400ms - Times executed: 28 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2s400ms - Times executed: 28 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059714438308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:20:04 Duration: 58ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '236785135', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059714438308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:28:04 Duration: 55ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '2116341431', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059714438308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:00:03 Duration: 49ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '236785135', $7 = '0'
9 732ms 28 13ms 53ms 26ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059710817308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.resultuid > $5 AND c.nonliquid = $6 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming bind #9
Day Hour Count Duration Avg duration 05 28 732ms 26ms [ User: postgres - Total duration: 281ms - Times executed: 28 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 281ms - Times executed: 28 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059710817308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.resultuid > $5 AND c.nonliquid = $6 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:16:04 Duration: 53ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '3', $4 = '3', $5 = '1507358751', $6 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059710817308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.resultuid > $5 AND c.nonliquid = $6 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:16:04 Duration: 46ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '3', $4 = '3', $5 = '1577132751', $6 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059710817308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.resultuid > $5 AND c.nonliquid = $6 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:28:04 Duration: 46ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '3', $4 = '3', $5 = '1507358751', $6 = '0'
10 717ms 28 15ms 53ms 25ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059725121308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming bind #10
Day Hour Count Duration Avg duration 05 28 717ms 25ms [ User: postgres - Total duration: 12ms - Times executed: 28 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 12ms - Times executed: 28 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059725121308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:52:04 Duration: 53ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '0', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059725121308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:16:04 Duration: 44ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '0', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059725121308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:48:04 Duration: 40ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '0', $7 = '0'
11 702ms 28 11ms 62ms 25ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059711596308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming bind #11
Day Hour Count Duration Avg duration 05 28 702ms 25ms [ User: postgres - Total duration: 674ms - Times executed: 28 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 674ms - Times executed: 28 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059711596308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:16:04 Duration: 62ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '1373285415', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059711596308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:28:04 Duration: 60ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '1373285415', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059711596308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:16:04 Duration: 37ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-1705839881', $7 = '0'
12 679ms 28 10ms 74ms 24ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059720124308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming bind #12
Day Hour Count Duration Avg duration 05 28 679ms 24ms [ User: postgres - Total duration: 546ms - Times executed: 28 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 546ms - Times executed: 28 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059720124308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:04:04 Duration: 74ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '2081333767', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059720124308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:16:04 Duration: 42ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '2081333767', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059720124308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:52:05 Duration: 42ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '2081333767', $7 = '0'
13 662ms 28 10ms 51ms 23ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059722409308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming bind #13
Day Hour Count Duration Avg duration 05 28 662ms 23ms [ User: postgres - Total duration: 1s413ms - Times executed: 28 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s413ms - Times executed: 28 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059722409308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:04:04 Duration: 51ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-1586187433', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059722409308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:32:04 Duration: 50ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '596483151', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059722409308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:16:04 Duration: 44ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-1586187433', $7 = '0'
14 618ms 28 10ms 48ms 22ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059706590308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming bind #14
Day Hour Count Duration Avg duration 05 28 618ms 22ms [ User: postgres - Total duration: 1s411ms - Times executed: 28 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s411ms - Times executed: 28 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059706590308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:28:04 Duration: 48ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '136048135', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059706590308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:32:04 Duration: 34ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '13966855', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059706590308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:40:05 Duration: 27ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '136048135', $7 = '0'
15 606ms 28 10ms 52ms 21ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059715831308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming bind #15
Day Hour Count Duration Avg duration 05 28 606ms 21ms [ User: postgres - Total duration: 1s471ms - Times executed: 28 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s471ms - Times executed: 28 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059715831308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:00:03 Duration: 52ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-508697153', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059715831308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:28:04 Duration: 39ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-1786988993', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059715831308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:32:04 Duration: 39ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-1786988993', $7 = '0'
16 558ms 14 18ms 81ms 39ms /*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059720124308 AND patternlengthbars >= 20 AND averagequality >= 0.0 AND (timequality >= 0.0 OR timequality = - 1) AND errormargin >= 0.0 AND 1 - noise >= 0.0 AND s.nonliquid = 0 AND PatternID & 39 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND PatternEndPrice = - 1 AND a.resultuid > 605848914119794302 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, averagequality DESC LIMIT 50;Times Reported Time consuming bind #16
Day Hour Count Duration Avg duration 05 14 558ms 39ms [ User: postgres - Total duration: 37ms - Times executed: 14 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 37ms - Times executed: 14 ]
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059720124308 AND patternlengthbars >= 20 AND averagequality >= 0.0 AND (timequality >= 0.0 OR timequality = - 1) AND errormargin >= 0.0 AND 1 - noise >= 0.0 AND s.nonliquid = 0 AND PatternID & 39 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND PatternEndPrice = - 1 AND a.resultuid > 605848914119794302 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, averagequality DESC LIMIT 50;
Date: 2025-03-31 05:04:04 Duration: 81ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059720124308 AND patternlengthbars >= 20 AND averagequality >= 0.0 AND (timequality >= 0.0 OR timequality = - 1) AND errormargin >= 0.0 AND 1 - noise >= 0.0 AND s.nonliquid = 0 AND PatternID & 39 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND PatternEndPrice = - 1 AND a.resultuid > 605848914119794302 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, averagequality DESC LIMIT 50;
Date: 2025-03-31 05:20:04 Duration: 74ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059720124308 AND patternlengthbars >= 20 AND averagequality >= 0.0 AND (timequality >= 0.0 OR timequality = - 1) AND errormargin >= 0.0 AND 1 - noise >= 0.0 AND s.nonliquid = 0 AND PatternID & 39 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND PatternEndPrice = - 1 AND a.resultuid > 605848914119794302 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, averagequality DESC LIMIT 50;
Date: 2025-03-31 05:24:05 Duration: 53ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
17 539ms 28 10ms 40ms 19ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059758978308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming bind #17
Day Hour Count Duration Avg duration 05 28 539ms 19ms [ User: postgres - Total duration: 3s957ms - Times executed: 28 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 3s957ms - Times executed: 28 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059758978308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:00:04 Duration: 40ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-1775585865', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059758978308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:20:05 Duration: 29ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-1775585865', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059758978308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:16:04 Duration: 25ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-1775585865', $7 = '0'
18 532ms 16 28ms 44ms 33ms with sym_info as ( ;Times Reported Time consuming bind #18
Day Hour Count Duration Avg duration 05 16 532ms 33ms [ User: postgres - Total duration: 21s556ms - Times executed: 16 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 21s556ms - Times executed: 16 ]
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with sym_info as ( ;
Date: 2025-03-31 05:52:01 Duration: 44ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238 parameters: $1 = '692', $2 = 'Forex', $3 = 'Forex', $4 = '692', $5 = 'Forex', $6 = '692', $7 = '692', $8 = 'Forex', $9 = '692'
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with sym_info as ( ;
Date: 2025-03-31 05:36:44 Duration: 44ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238 parameters: $1 = '620', $2 = 'Forex', $3 = 'Forex', $4 = '620', $5 = 'Forex', $6 = '620', $7 = '620', $8 = 'Forex', $9 = '620'
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with sym_info as ( ;
Date: 2025-03-31 05:51:46 Duration: 43ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238 parameters: $1 = '617', $2 = 'Forex', $3 = 'Forex', $4 = '617', $5 = 'Forex', $6 = '617', $7 = '617', $8 = 'Forex', $9 = '617'
19 529ms 28 10ms 27ms 18ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059709228308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming bind #19
Day Hour Count Duration Avg duration 05 28 529ms 18ms [ User: postgres - Total duration: 1s651ms - Times executed: 28 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s651ms - Times executed: 28 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059709228308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:16:04 Duration: 27ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '724909295', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059709228308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:32:04 Duration: 26ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-1044195697', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059709228308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-03-31 05:20:05 Duration: 24ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '724909295', $7 = '0'
20 522ms 12 28ms 61ms 43ms /*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059709228308 AND patternlengthbars >= 20 AND averagequality >= 0.0 AND (timequality >= 0.0 OR timequality = - 1) AND errormargin >= 0.0 AND 1 - noise >= 0.0 AND s.nonliquid = 0 AND PatternID & 39 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND PatternEndPrice = - 1 AND a.resultuid > 605863598006018302 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, averagequality DESC LIMIT 50;Times Reported Time consuming bind #20
Day Hour Count Duration Avg duration 05 12 522ms 43ms [ User: postgres - Total duration: 12ms - Times executed: 12 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 12ms - Times executed: 12 ]
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059709228308 AND patternlengthbars >= 20 AND averagequality >= 0.0 AND (timequality >= 0.0 OR timequality = - 1) AND errormargin >= 0.0 AND 1 - noise >= 0.0 AND s.nonliquid = 0 AND PatternID & 39 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND PatternEndPrice = - 1 AND a.resultuid > 605863598006018302 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, averagequality DESC LIMIT 50;
Date: 2025-03-31 05:20:04 Duration: 61ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059709228308 AND patternlengthbars >= 20 AND averagequality >= 0.0 AND (timequality >= 0.0 OR timequality = - 1) AND errormargin >= 0.0 AND 1 - noise >= 0.0 AND s.nonliquid = 0 AND PatternID & 39 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND PatternEndPrice = - 1 AND a.resultuid > 605863598006018302 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, averagequality DESC LIMIT 50;
Date: 2025-03-31 05:28:05 Duration: 61ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059709228308 AND patternlengthbars >= 20 AND averagequality >= 0.0 AND (timequality >= 0.0 OR timequality = - 1) AND errormargin >= 0.0 AND 1 - noise >= 0.0 AND s.nonliquid = 0 AND PatternID & 39 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND PatternEndPrice = - 1 AND a.resultuid > 605863598006018302 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, averagequality DESC LIMIT 50;
Date: 2025-03-31 05:12:04 Duration: 53ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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Events
Log levels
Key values
- 359,379 Log entries
Events distribution
Key values
- 0 PANIC entries
- 0 FATAL entries
- 23 ERROR entries
- 0 WARNING entries
Most Frequent Errors/Events
Key values
- 23 Max number of times the same event was reported
- 23 Total events found
Rank Times reported Error 1 23 ERROR: duplicate key value violates unique constraint "..."
Times Reported Most Frequent Error / Event #1
Day Hour Count Mar 31 05 23 - ERROR: duplicate key value violates unique constraint "idx_sa_hist_conscandles_symbolid_datetime_direction"
Detail: Key (symbolid, datetime, direction)=(515840224274507300, 2025-03-10 12:00:00, -1) already exists.
Statement: insert into sa_hist_consecutivecandles (symbolid, datetime, image, qty, percentile, direction, height) values ($1,$2,$3,$4,$5,$6,$7)Date: 2025-03-31 05:30:06 Database: acaweb_fx Application: [unknown] User: postgres Remote: 127.0.0.1