SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1), results AS ( SELECT DISTINCT ON (s.symbolid) kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, 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 rar.age IS NOT NULL THEN rar.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM keylevels_results kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $1 AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON kr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on kr.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 kr.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 relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND (kr.simulation = 0 OR kr.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 s.symbol in ($13)) AND ($14 = 0 OR p.patternname in ($15)) AND ($16 = 0 OR kr.patternclassid in ($17, $18)) AND ($19 = 0 OR kr.patternlengthbars <= $20) ORDER BY symbolid, identified DESC, patternlengthbars DESC ) SELECT * from results WHERE (FALSE = $21 OR relevant = 1) AND ($22 = 0 OR age <= $23) ORDER BY identified DESC, length DESC;

Date: 2021-05-19 12:00:34
Duration: 0ms
Database: acaweb_fx
User: postgres

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SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1), results AS ( SELECT DISTINCT ON (s.symbolid) fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, 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, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM fibonacci_results fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $1 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 OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = fr.resultuid WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ($2 = 0 OR s.timegranularity in ($3)) AND ($4 = 0 OR s.exchange in ($5)) AND ($6 = 0 OR s.symbol in ($7)) AND ($8 = 0 OR fr.pattern in ($9)) AND ($10 = 0 OR fr.patternlengthbars <= $11) AND ($12 = 0 OR ($13 = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ($14 = 2 AND fr.timed < cast('1970-01-01' as timestamp))) ORDER BY symbolid, identified DESC, patternlengthbars DESC ) SELECT * from results WHERE (FALSE = $15 OR relevant = 1) AND ($16 = 0 OR age <= $17) ORDER BY identified DESC, length DESC;

Date: 2021-05-19 12:01:56
Duration: 0ms
Database: acaweb_fx
User: postgres

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)) AND breakout >= 0.0 AND patternendtime = LatestBarAtBreakoutTime AND patternlengthbars >= 20 AND patternquality >= 0.3 AND initialtrend >= 0.0 AND symmetry >= 0.0 AND noise <= 1.0 AND volumeincrease >= 0.0 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 513856915 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;

Date: 2021-05-19 12:00:07
Duration: 0ms
Database: acaweb_fx
User: postgres

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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: 2021-05-19 12:08:27
Duration: 892ms
Database: acaweb_fx
User: postgres

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: 2021-05-19 12:31:27
Duration: 309ms
Database: acaweb_fx
User: postgres

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: 2021-05-19 12:16:14
Duration: 273ms
Database: acaweb_fx
User: postgres

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select * from PowerStatsLatestPRFPrice ($1, $2);

Date: 2021-05-19 12:05:07
Duration: 0ms
Database: acaweb_fx
User: postgres

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WITH a AS ( SELECT *, row_number() OVER (PARTITION BY symbolid, direction ORDER BY datetime DESC) r FROM sa_hist_consecutivecandles ) SELECT DISTINCT a.symbolid, a.qty, a.percentile, a.direction FROM a INNER JOIN symbols s on a.symbolid = s.symbolid INNER JOIN autochartist_stocklist aus on s.symbolid = aus.symbolid WHERE aus.Enabled = 1 AND a.r = 1 AND aus.RecognitionEngine ILIKE 'LEGACYFXMT5 - 1';

Date: 2021-05-19 12:27:36
Duration: 347ms
Database: acaweb_fx
User: postgres

WITH a AS ( SELECT *, row_number() OVER (PARTITION BY symbolid, direction ORDER BY datetime DESC) r FROM sa_hist_consecutivecandles ) SELECT DISTINCT a.symbolid, a.qty, a.percentile, a.direction FROM a INNER JOIN symbols s on a.symbolid = s.symbolid INNER JOIN autochartist_stocklist aus on s.symbolid = aus.symbolid WHERE aus.Enabled = 1 AND a.r = 1 AND aus.RecognitionEngine ILIKE 'MILLENNIUMPF - 1';

Date: 2021-05-19 12:27:57
Duration: 337ms
Database: acaweb_fx
User: postgres

WITH a AS ( SELECT *, row_number() OVER (PARTITION BY symbolid, direction ORDER BY datetime DESC) r FROM sa_hist_consecutivecandles ) SELECT DISTINCT a.symbolid, a.qty, a.percentile, a.direction FROM a INNER JOIN symbols s on a.symbolid = s.symbolid INNER JOIN autochartist_stocklist aus on s.symbolid = aus.symbolid WHERE aus.Enabled = 1 AND a.r = 1 AND aus.RecognitionEngine ILIKE 'XM - 1';

Date: 2021-05-19 12:28:40
Duration: 335ms
Database: acaweb_fx
User: postgres

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SELECT DISTINCT a.resultuid, a.breakoutbars, a.patternid, CAST(a.x0 as timestamp) as x0, CAST(a.x1 as timestamp) as x1, CAST(x2 as timestamp) as x2, CASE WHEN (x3 != '' and x3 != '0') THEN CAST(x3 as timestamp) ELSE CAST('1900-01-01' as timestamp) END as x3, CASE WHEN (x4 != '' and x4 != '0') THEN CAST(x4 as timestamp) ELSE CAST('1900-01-01' as timestamp) END as x4, CASE WHEN (x5 != '' and x5 != '0') THEN CAST(x5 as timestamp) ELSE CAST('1900-01-01' as timestamp) END as x5, CASE WHEN (x6 != '' and x6 != '0') THEN CAST(x6 as timestamp) ELSE CAST('1900-01-01' as timestamp) END as x6, CASE WHEN (x7 != '' and x7 != '0') THEN CAST(x7 as timestamp) ELSE CAST('1900-01-01' as timestamp) END as x7, CASE WHEN (x8 != '' and x8 != '0') THEN CAST(x8 as timestamp) ELSE CAST('1900-01-01' as timestamp) END as x8, CASE WHEN (x9 != '' and x9 != '0') THEN CAST(x9 as timestamp) ELSE CAST('1900-01-01' as timestamp) END as x9, CAST(a.atbaridentified as timestamp) as atbaridentified, CAST(a.patternstarttime as timestamp) as patternstarttime, a.breakoutprice, a.symbolid, a.approachingregion, a.patternprice, a.errorMargin, a.bandwidth, a.qtytp, a.patternlengthbars, a.symbolid, a.uniquepointsvalue, a.predictionpricefrom, a.predictionpriceto, a.breakout, a.direction, a.furthestPrice, a.approachingtimestamp, a.atPriceIdentified FROM keylevels_results a INNER JOIN symbols s on a.symbolid = s.symbolid INNER JOIN autochartist_stocklist aus on s.symbolid = aus.symbolid INNER JOIN relevance_keylevels_results rkl on a.resultuid = rkl.resultuid WHERE aus.Enabled = 1 AND rkl.relevant = 1 AND aus.RecognitionEngine ILIKE 'legacyfxmt5 - 1';

Date: 2021-05-19 12:27:36
Duration: 313ms
Database: acaweb_fx
User: postgres

SELECT DISTINCT a.resultuid, a.breakoutbars, a.patternid, CAST(a.x0 as timestamp) as x0, CAST(a.x1 as timestamp) as x1, CAST(x2 as timestamp) as x2, CASE WHEN (x3 != '' and x3 != '0') THEN CAST(x3 as timestamp) ELSE CAST('1900-01-01' as timestamp) END as x3, CASE WHEN (x4 != '' and x4 != '0') THEN CAST(x4 as timestamp) ELSE CAST('1900-01-01' as timestamp) END as x4, CASE WHEN (x5 != '' and x5 != '0') THEN CAST(x5 as timestamp) ELSE CAST('1900-01-01' as timestamp) END as x5, CASE WHEN (x6 != '' and x6 != '0') THEN CAST(x6 as timestamp) ELSE CAST('1900-01-01' as timestamp) END as x6, CASE WHEN (x7 != '' and x7 != '0') THEN CAST(x7 as timestamp) ELSE CAST('1900-01-01' as timestamp) END as x7, CASE WHEN (x8 != '' and x8 != '0') THEN CAST(x8 as timestamp) ELSE CAST('1900-01-01' as timestamp) END as x8, CASE WHEN (x9 != '' and x9 != '0') THEN CAST(x9 as timestamp) ELSE CAST('1900-01-01' as timestamp) END as x9, CAST(a.atbaridentified as timestamp) as atbaridentified, CAST(a.patternstarttime as timestamp) as patternstarttime, a.breakoutprice, a.symbolid, a.approachingregion, a.patternprice, a.errorMargin, a.bandwidth, a.qtytp, a.patternlengthbars, a.symbolid, a.uniquepointsvalue, a.predictionpricefrom, a.predictionpriceto, a.breakout, a.direction, a.furthestPrice, a.approachingtimestamp, a.atPriceIdentified FROM keylevels_results a INNER JOIN symbols s on a.symbolid = s.symbolid INNER JOIN autochartist_stocklist aus on s.symbolid = aus.symbolid INNER JOIN relevance_keylevels_results rkl on a.resultuid = rkl.resultuid WHERE aus.Enabled = 1 AND rkl.relevant = 1 AND aus.RecognitionEngine ILIKE 'xm - 1';

Date: 2021-05-19 12:28:40
Duration: 201ms
Database: acaweb_fx
User: postgres

SELECT DISTINCT a.resultuid, a.breakoutbars, a.patternid, CAST(a.x0 as timestamp) as x0, CAST(a.x1 as timestamp) as x1, CAST(x2 as timestamp) as x2, CASE WHEN (x3 != '' and x3 != '0') THEN CAST(x3 as timestamp) ELSE CAST('1900-01-01' as timestamp) END as x3, CASE WHEN (x4 != '' and x4 != '0') THEN CAST(x4 as timestamp) ELSE CAST('1900-01-01' as timestamp) END as x4, CASE WHEN (x5 != '' and x5 != '0') THEN CAST(x5 as timestamp) ELSE CAST('1900-01-01' as timestamp) END as x5, CASE WHEN (x6 != '' and x6 != '0') THEN CAST(x6 as timestamp) ELSE CAST('1900-01-01' as timestamp) END as x6, CASE WHEN (x7 != '' and x7 != '0') THEN CAST(x7 as timestamp) ELSE CAST('1900-01-01' as timestamp) END as x7, CASE WHEN (x8 != '' and x8 != '0') THEN CAST(x8 as timestamp) ELSE CAST('1900-01-01' as timestamp) END as x8, CASE WHEN (x9 != '' and x9 != '0') THEN CAST(x9 as timestamp) ELSE CAST('1900-01-01' as timestamp) END as x9, CAST(a.atbaridentified as timestamp) as atbaridentified, CAST(a.patternstarttime as timestamp) as patternstarttime, a.breakoutprice, a.symbolid, a.approachingregion, a.patternprice, a.errorMargin, a.bandwidth, a.qtytp, a.patternlengthbars, a.symbolid, a.uniquepointsvalue, a.predictionpricefrom, a.predictionpriceto, a.breakout, a.direction, a.furthestPrice, a.approachingtimestamp, a.atPriceIdentified FROM keylevels_results a INNER JOIN symbols s on a.symbolid = s.symbolid INNER JOIN autochartist_stocklist aus on s.symbolid = aus.symbolid INNER JOIN relevance_keylevels_results rkl on a.resultuid = rkl.resultuid WHERE aus.Enabled = 1 AND rkl.relevant = 1 AND aus.RecognitionEngine ILIKE 'xm - 2';

Date: 2021-05-19 12:29:01
Duration: 200ms
Database: acaweb_fx
User: postgres

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SELECT DISTINCT a.resultuid, a.resultid, a.patternlengthbars, a.patternendtime, a.predictionpriceto, a.predictionpricefrom, a.direction, a.breakout, a.bandwidth, a.resy0, a.resy1, a.supporty0, a.supporty1, a.resx0, a.resx1, a.supportx0, a.supportx1, a.patternendprice, a.symbolid, a.resgradient, a.supportgradient FROM autochartist_results a INNER JOIN symbols s on a.symbolid = s.symbolid INNER JOIN autochartist_stocklist aus on s.symbolid = aus.symbolid INNER JOIN relevance_autochartist_results rev on a.resultuid = rev.resultuid WHERE aus.Enabled = 1 AND rev.relevant = 1 AND aus.RecognitionEngine ILIKE 'xm - 1';

Date: 2021-05-19 12:28:39
Duration: 610ms
Database: acaweb_fx
User: postgres

SELECT DISTINCT a.resultuid, a.resultid, a.patternlengthbars, a.patternendtime, a.predictionpriceto, a.predictionpricefrom, a.direction, a.breakout, a.bandwidth, a.resy0, a.resy1, a.supporty0, a.supporty1, a.resx0, a.resx1, a.supportx0, a.supportx1, a.patternendprice, a.symbolid, a.resgradient, a.supportgradient FROM autochartist_results a INNER JOIN symbols s on a.symbolid = s.symbolid INNER JOIN autochartist_stocklist aus on s.symbolid = aus.symbolid INNER JOIN relevance_autochartist_results rev on a.resultuid = rev.resultuid WHERE aus.Enabled = 1 AND rev.relevant = 1 AND aus.RecognitionEngine ILIKE 'xm - 2';

Date: 2021-05-19 12:29:00
Duration: 553ms
Database: acaweb_fx
User: postgres

SELECT DISTINCT a.resultuid, a.resultid, a.patternlengthbars, a.patternendtime, a.predictionpriceto, a.predictionpricefrom, a.direction, a.breakout, a.bandwidth, a.resy0, a.resy1, a.supporty0, a.supporty1, a.resx0, a.resx1, a.supportx0, a.supportx1, a.patternendprice, a.symbolid, a.resgradient, a.supportgradient FROM autochartist_results a INNER JOIN symbols s on a.symbolid = s.symbolid INNER JOIN autochartist_stocklist aus on s.symbolid = aus.symbolid INNER JOIN relevance_autochartist_results rev on a.resultuid = rev.resultuid WHERE aus.Enabled = 1 AND rev.relevant = 1 AND aus.RecognitionEngine ILIKE 'legacyfxmt5 - 1';

Date: 2021-05-19 12:27:35
Duration: 368ms
Database: acaweb_fx
User: postgres

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select updateresultsmaterializedview ();

Date: 2021-05-19 12:02:09
Duration: 1s571ms
Database: acaweb_fx
User: postgres

select updateresultsmaterializedview ();

Date: 2021-05-19 12:32:10
Duration: 1s554ms
Database: acaweb_fx
User: postgres

select updateresultsmaterializedview ();

Date: 2021-05-19 12:47:09
Duration: 1s542ms
Database: acaweb_fx
User: postgres

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) OR ((s.symbol ilike '%xaueur%' AND timegranularity = 1440))) AND breakout >= 0.1 AND patternendtime = LatestBarAtBreakoutTime AND patternlengthbars >= 20 AND patternquality >= 0.3 AND initialtrend >= 0.1 AND symmetry >= 0.0 AND noise <= 0.8 AND volumeincrease >= 0.0 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 513881256 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;

Date: 2021-05-19 12:18:08
Duration: 0ms
Database: acaweb_fx
User: postgres

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SELECT tl.timezone langTimezone, t.timezone as timezone, (cast(substring(t.gmoffset, 0, 4) as double precision) * 60 + cast(substring(t.gmoffset, 5, 2) as double precision)) / 60 as gmoffset FROM timezones_vi_VN tl INNER JOIN timezones t ON tl.timezoneid = t.timezoneid ORDER BY t.timezone;

Date: 2021-05-19 12:24:47
Duration: 0ms
Database: acaweb_fx
User: postgres

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) OR ((s.symbol ilike '%soybean_u7%' AND timegranularity = 240)) OR ((s.symbol ilike '%soybean_q7%' AND timegranularity <= 1440)) OR ((s.symbol ilike '%soybean_u7%' AND timegranularity <= 1440)) OR ((s.symbol ilike '%usdchf%' AND timegranularity = 240)) OR ((s.symbol ilike '%usdchf%' AND timegranularity = 60)) OR ((s.symbol ilike '%chfjpy%' AND timegranularity = 240)) OR ((s.symbol ilike '%chfjpy%' AND timegranularity = 60))) AND breakout >= 0.6 AND patternendtime = LatestBarAtBreakoutTime AND patternlengthbars >= 80 AND patternquality >= 0.6 AND initialtrend >= 0.0 AND symmetry >= 0.0 AND noise <= 1.0 AND volumeincrease >= 0.0 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 511838882 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;

Date: 2021-05-19 12:02:08
Duration: 0ms
Database: acaweb_fx
User: postgres

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) OR ((s.symbol ilike '%audchf%' AND timegranularity = 1440)) OR ((s.symbol ilike '%audjpy%' AND timegranularity = 1440)) OR ((s.symbol ilike '%audnzd%' AND timegranularity = 1440)) OR ((s.symbol ilike '%audusd%' AND timegranularity = 1440)) OR ((s.symbol ilike '%audcad%' AND timegranularity = 240)) OR ((s.symbol ilike '%gbpaud%' AND timegranularity = 1440))) AND breakout >= 0.0 AND patternendtime = LatestBarAtBreakoutTime AND patternlengthbars >= 20 AND patternquality >= 0.3 AND initialtrend >= 0.0 AND symmetry >= 0.0 AND noise <= 1.0 AND volumeincrease >= 0.0 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 513622198 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;

Date: 2021-05-19 12:32:47
Duration: 0ms
Database: acaweb_fx
User: postgres

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when 1440 then 1 when 240 then 3 when 60 then 4 when 30 then 5 when 15 then 5 end)) ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;

Date: 2021-05-19 12:38:48
Duration: 0ms
Database: acaweb_fx
User: postgres

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