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High Memory usage after 444 version with iceberg connector #21947

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sachleen0700 opened this issue May 13, 2024 · 4 comments
Open

High Memory usage after 444 version with iceberg connector #21947

sachleen0700 opened this issue May 13, 2024 · 4 comments
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iceberg Iceberg connector

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@sachleen0700
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same query running on v443 is using less memory while versions after 443 is using hight memory for the same query, using iceberg connector
@findinpath
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@sachleen0700 do you have any more data to share to potentially identify the issue?

A good start would be the query plans between the version which you considered better and 443.

Do you maybe have a reproduction scenario?

@findinpath findinpath added the iceberg Iceberg connector label May 15, 2024
@sachleen0700
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@findinpath
query plan in version 443:

Trino version: 443 Fragment 0 [SINGLE] Output layout: [expr_537, expr_531, expr_1319, expr_1320, expr_532, expr_1321, expr_1322, expr_539, expr_538, expr_535, id_610, id_4] Output partitioning: SINGLE [] Output[columnNames = [city, Start_date, utmmedium, utmsource, platform, LOB, Source2, Source_Category, Assigned_lead_CT, Walkin_type, app_id, context_id]] │ Layout: [expr_537:varchar, expr_531:date, expr_1319:varchar(16), expr_1320:varchar(10), expr_532:varchar(6), expr_1321:varchar(9), expr_1322:varchar, expr_539:varchar(7), expr_538:varchar(12), expr_535:varchar(3), id_610:integer, id_4:integer] │ Estimates: {rows: 100 (49.80kB), cpu: 0, memory: 0B, network: 0B} │ city := expr_537 │ Start_date := expr_531 │ utmmedium := expr_1319 │ utmsource := expr_1320 │ platform := expr_532 │ LOB := expr_1321 │ Source2 := expr_1322 │ Source_Category := expr_539 │ Assigned_lead_CT := expr_538 │ Walkin_type := expr_535 │ app_id := id_610 │ context_id := id_4 └─ TopN[count = 100, orderBy = [expr_531 DESC NULLS LAST]] │ Layout: [expr_537:varchar, expr_531:date, expr_1319:varchar(16), expr_1320:varchar(10), expr_532:varchar(6), expr_1321:varchar(9), expr_1322:varchar, expr_539:varchar(7), expr_538:varchar(12), expr_535:varchar(3), id_610:integer, id_4:integer] │ Estimates: {rows: 100 (49.80kB), cpu: ?, memory: ?, network: ?} └─ LocalExchange[partitioning = SINGLE] │ Layout: [expr_537:varchar, expr_531:date, expr_1319:varchar(16), expr_1320:varchar(10), expr_532:varchar(6), expr_1321:varchar(9), expr_1322:varchar, expr_539:varchar(7), expr_538:varchar(12), expr_535:varchar(3), id_610:integer, id_4:integer] │ Estimates: {rows: ? (?), cpu: 0, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [1]] Layout: [expr_537:varchar, expr_531:date, expr_1319:varchar(16), expr_1320:varchar(10), expr_532:varchar(6), expr_1321:varchar(9), expr_1322:varchar, expr_539:varchar(7), expr_538:varchar(12), expr_535:varchar(3), id_610:integer, id_4:integer] Fragment 1 [HASH] Output layout: [expr_537, expr_531, expr_1319, expr_1320, expr_532, expr_1321, expr_1322, expr_539, expr_538, expr_535, id_610, id_4] Output partitioning: SINGLE [] TopNPartial[count = 100, orderBy = [expr_531 DESC NULLS LAST]] │ Layout: [expr_537:varchar, expr_531:date, expr_1319:varchar(16), expr_1320:varchar(10), expr_532:varchar(6), expr_1321:varchar(9), expr_1322:varchar, expr_539:varchar(7), expr_538:varchar(12), expr_535:varchar(3), id_610:integer, id_4:integer] └─ Aggregate[type = FINAL, keys = [expr_537, expr_531, expr_1319, expr_1320, expr_532, expr_1321, expr_1322, expr_539, expr_538, expr_535, id_610, id_4]] │ Layout: [expr_537:varchar, expr_531:date, expr_1319:varchar(16), expr_1320:varchar(10), expr_532:varchar(6), expr_1321:varchar(9), expr_1322:varchar, expr_539:varchar(7), expr_538:varchar(12), expr_535:varchar(3), id_610:integer, id_4:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=varchar, name=expr_537], SymbolReference[type=date, name=expr_531], SymbolReference[type=varchar(16), name=expr_1319], SymbolReference[type=varchar(10), name=expr_1320], SymbolReference[type=varchar(6), name=expr_532], SymbolReference[type=varchar(9), name=expr_1321], SymbolReference[type=varchar, name=expr_1322], SymbolReference[type=varchar(7), name=expr_539], SymbolReference[type=varchar(12), name=expr_538], SymbolReference[type=varchar(3), name=expr_535], SymbolReference[type=integer, name=id_610], SymbolReference[type=integer, name=id_4]]] │ Layout: [expr_537:varchar, expr_531:date, expr_1319:varchar(16), expr_1320:varchar(10), expr_532:varchar(6), expr_1321:varchar(9), expr_1322:varchar, expr_539:varchar(7), expr_538:varchar(12), expr_535:varchar(3), id_610:integer, id_4:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [2]] Layout: [expr_537:varchar, expr_531:date, expr_1319:varchar(16), expr_1320:varchar(10), expr_532:varchar(6), expr_1321:varchar(9), expr_1322:varchar, expr_539:varchar(7), expr_538:varchar(12), expr_535:varchar(3), id_610:integer, id_4:integer] Fragment 2 [HASH] Output layout: [expr_537, expr_531, expr_1319, expr_1320, expr_532, expr_1321, expr_1322, expr_539, expr_538, expr_535, id_610, id_4] Output partitioning: HASH [expr_537, expr_531, expr_1319, expr_1320, expr_532, expr_1321, expr_1322, expr_539, expr_538, expr_535, id_610, id_4] Aggregate[type = PARTIAL, keys = [expr_537, expr_531, expr_1319, expr_1320, expr_532, expr_1321, expr_1322, expr_539, expr_538, expr_535, id_610, id_4]] │ Layout: [expr_537:varchar, expr_531:date, expr_1319:varchar(16), expr_1320:varchar(10), expr_532:varchar(6), expr_1321:varchar(9), expr_1322:varchar, expr_539:varchar(7), expr_538:varchar(12), expr_535:varchar(3), id_610:integer, id_4:integer] └─ Project[] │ Layout: [expr_539:varchar(7), expr_538:varchar(12), expr_1319:varchar(16), expr_532:varchar(6), id_4:integer, expr_531:date, expr_1320:varchar(10), id_610:integer, expr_1321:varchar(9), expr_537:varchar, expr_1322:varchar, expr_535:varchar(3)] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ expr_1319 := (CASE WHEN (utm_medium = varchar 'truebil') THEN varchar(16) 'truebil' WHEN (utm_source = varchar 'truebil') THEN varchar(16) 'truebil' WHEN (utm_term = varchar 'TruebilBudgetRedirect') THEN varchar(16) 'truebil' WHEN (CAST(id_610 AS varchar) = CAST(id_4 AS varchar)) THEN CAST(expr_1316 AS varchar(16)) WHEN ((utm_source = varchar 'direct') AND (utm_medium IS NULL)) THEN varchar(16) 'Direct' WHEN ((utm_source = varchar 'direct') AND (utm_medium = varchar '')) THEN varchar(16) 'Direct' WHEN ((utm_source = varchar 'organic') AND (utm_medium = varchar '')) THEN varchar(16) 'Organic' WHEN ((utm_source = varchar 'organic') AND (utm_medium IS NULL)) THEN varchar(16) 'Organic' WHEN ((utm_source = varchar '') AND (utm_medium = varchar '')) THEN varchar(16) 'Organic' WHEN ((utm_source IS NULL) AND (utm_medium IS NULL)) THEN varchar(16) 'Organic' WHEN (utm_medium = varchar 'fbad') THEN varchar(16) 'Facebook' WHEN (utm_medium = varchar 'FBboost') THEN varchar(16) 'Facebook' WHEN (utm_medium = varchar 'cpm') THEN varchar(16) 'Facebook' WHEN (utm_medium = varchar 'affiliate_demand') THEN varchar(16) 'Affiliate' WHEN (utm_source IN varchar 'Taboola', varchar 'adgebra', varchar 'outbrain') THEN varchar(16) 'Native' WHEN (utm_medium = varchar 'partnerships') THEN varchar(16) 'Partnerships' WHEN ((utm_medium IN varchar 'gads_t_search', varchar 'gads_c_search', varchar 'gads_m_search', varchar 'bingads_c_search', varchar 'bingads_m_search', varchar 'bingads_t_search') AND system.builtin.$like(utm_source, LikePattern '[%Brand%]')) THEN varchar(16) 'SEM Brand' WHEN ((utm_medium IN varchar 'gads_t_search', varchar 'gads_c_search', varchar 'gads_m_search', varchar 'bingads_c_search', varchar 'bingads_m_search', varchar 'bingads_t_search') AND (NOT system.builtin.$like(utm_source, LikePattern '[%Brand%]'))) THEN varchar(16) 'SEM Non Brand' WHEN (system.builtin.$like(utm_medium, LikePattern '[%whatsapp%]') OR system.builtin.$like(utm_medium, LikePattern '[%sms%]') OR system.builtin.$like(utm_medium, LikePattern '[%push%]') OR system.builtin.$like(utm_medium, LikePattern '[%whatsapp=utm_campaign=supply-lead-created_abn1nkm%]') OR system.builtin.$like(utm_medium, LikePattern '[%webpush%]') OR system.builtin.$like(utm_medium, LikePattern '[%WhatsappGetDetailsTD%]') OR system.builtin.$like(utm_medium, LikePattern '[%whatsapp_promotional%]') OR system.builtin.$like(utm_medium, LikePattern '[%email%]') OR system.builtin.$like(utm_source, LikePattern '[%whatsapp_share%]')) THEN varchar(16) 'CRM' WHEN (utm_medium = varchar 'gads_t_video') THEN varchar(16) 'Youtube' WHEN (utm_medium = varchar 'gads_c_video') THEN varchar(16) 'Youtube' WHEN (utm_medium = varchar 'gads_m_video') THEN varchar(16) 'Youtube' WHEN (utm_medium = varchar 'gads_m_discovery') THEN varchar(16) 'Discovery' WHEN (utm_medium = varchar 'gads_t_discovery') THEN varchar(16) 'Discovery' WHEN (utm_medium = varchar 'gads_c_discovery') THEN varchar(16) 'Discovery' WHEN (utm_medium = varchar 'gads_t_display') THEN varchar(16) 'Display' WHEN (utm_medium = varchar 'gads_c_display') THEN varchar(16) 'Display' WHEN (utm_medium = varchar 'gads_m_display') THEN varchar(16) 'Display' WHEN (utm_medium = varchar 'affiliate') THEN varchar(16) 'Supply_Affiliate' ELSE varchar(16) 'Others' END) │ expr_1320 := (CASE WHEN ((utm_medium IN varchar 'fbad', varchar 'FBboost', varchar 'gads_m_display', varchar 'gads_c_display', varchar 'gads_t_display', varchar 'gads_m_video', varchar 'gads_c_video', varchar 'gads_t_video', varchar 'gads_c_discovery', varchar 'gads_t_discovery', varchar 'gads_m_discovery') AND system.builtin.$like(utm_source, LikePattern '[%RM%]')) THEN varchar(10) 'RM' WHEN ((utm_medium IN varchar 'fbad', varchar 'FBboost', varchar 'gads_m_display', varchar 'gads_c_display', varchar 'gads_t_display', varchar 'gads_m_video', varchar 'gads_c_video', varchar 'gads_t_video', varchar 'gads_c_discovery', varchar 'gads_t_discovery', varchar 'gads_m_discovery') AND (NOT system.builtin.$like(utm_source, LikePattern '[%RM%]'))) THEN varchar(10) 'PR' WHEN system.builtin.$like(utm_source, LikePattern '[%Remarketing%]') THEN varchar(10) 'RM' WHEN (utm_medium = varchar 'email') THEN varchar(10) 'email' WHEN (utm_medium = varchar 'sms') THEN varchar(10) 'sms' WHEN (utm_medium = varchar 'webpush') THEN varchar(10) 'Webpush' WHEN (utm_medium = varchar 'push') THEN varchar(10) 'Push' WHEN (utm_medium = varchar 'whatsapp') THEN varchar(10) 'Whatsapp' WHEN (utm_medium = varchar 'affiliate_demand') THEN varchar(10) 'Website' WHEN (CAST(expr_533 AS integer) IN integer '473', integer '1027', integer '1028', integer '1029', integer '1050', integer '1051', integer '1052', integer '1054', integer '1055', integer '1056', integer '1057') THEN varchar(10) 'MissedCall' WHEN (utm_source = varchar 'truebil') THEN varchar(10) 'truebil' ELSE varchar(10) 'Others' END) │ expr_1321 := (CASE WHEN (system.builtin.$like(utm_source, LikePattern '[%SPS%]') OR system.builtin.$like(utm_source, LikePattern '[%SPMS%]') OR (utm_medium = varchar 'affiliate')) THEN varchar(9) 'Cross LOB' ELSE varchar(9) 'Same LOB' END) │ expr_1322 := (CASE WHEN (expr_534 IN varchar 'buy_request', varchar 'buyrequest') THEN varchar 'buyrequest' WHEN (expr_534 IN varchar 'car_finance', varchar 'carfinance') THEN varchar 'carfinance' WHEN system.builtin.$like(system.builtin.lower(expr_534), LikePattern '[%callback%]') THEN varchar 'callback' WHEN (expr_534 IN varchar 'contact_us', varchar 'contactus') THEN varchar 'contactus' WHEN (expr_534 IN varchar 'deal_requested', varchar 'dealrequest') THEN varchar 'dealrequest' WHEN system.builtin.$like(system.builtin.lower(expr_534), LikePattern '[%direct%]') THEN varchar 'direct' WHEN system.builtin.$like(system.builtin.lower(expr_534), LikePattern '[%facebookleadform%]') THEN varchar 'facebookleadform' WHEN system.builtin.$like(system.builtin.lower(expr_534), LikePattern '[%filters%]') THEN varchar 'neutralpage' WHEN system.builtin.$like(system.builtin.lower(expr_534), LikePattern '[%neutral%]') THEN varchar 'neutralpage' WHEN (expr_534 IN varchar 'filters', varchar 'neutral_page') THEN varchar 'neutralpage' WHEN system.builtin.$like(system.builtin.lower(expr_534), LikePattern '[%googleleadform%]') THEN varchar 'googleleadform' WHEN system.builtin.$like(system.builtin.lower(expr_534), LikePattern '[%lead%]') THEN varchar 'lead' WHEN (expr_534 IN varchar 'message', varchar 'whatsapp') THEN varchar 'message' WHEN (expr_534 IN varchar 'notify_me', varchar 'notifyme') THEN varchar 'notifyme' WHEN system.builtin.$like(system.builtin.lower(expr_534), LikePattern '[%proxycontextmodel%]') THEN varchar 'proxycontextmodel' WHEN system.builtin.$like(system.builtin.lower(expr_534), LikePattern '[%reference%]') THEN varchar 'reference' WHEN system.builtin.$like(system.builtin.lower(expr_534), LikePattern '[%sell_to_buy_lead%]') THEN varchar 'lead' WHEN system.builtin.$like(system.builtin.lower(expr_534), LikePattern '[%shortlist%]') THEN varchar 'shortlist' WHEN (expr_534 IN varchar 'viewinspectionreport', varchar 'view_inspection_report') THEN varchar 'viewinspectionreport' WHEN system.builtin.$like(system.builtin.lower(expr_534), LikePattern '[%webarticle%]') THEN varchar 'webarticle' WHEN (expr_534 IN varchar 'PDP_PhotoGallery_360', varchar 'PDP_PhotoGallery_AllPhotos') THEN varchar 'imagegallery' WHEN ((expr_534 = varchar 'user_activity_log') AND (user_activity_type = varchar 'view_inspection_report')) THEN varchar 'viewinspectionreport' WHEN ((expr_534 = varchar 'user_activity_log') AND (user_activity_type = varchar 'view_more_car_images')) THEN varchar 'imagegallery' WHEN (expr_534 IS NULL) THEN varchar 'null' ELSE expr_534 END) └─ LeftJoin[criteria = (expr_1317 = expr_1318), distribution = PARTITIONED] │ Layout: [expr_539:varchar(7), expr_538:varchar(12), utm_medium:varchar, utm_term:varchar, expr_533:unknown, expr_532:varchar(6), id_4:integer, expr_531:date, expr_537:varchar, user_activity_type:varchar, expr_535:varchar(3), expr_534:varchar, utm_source:varchar, expr_1316:varchar(14), id_610:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} │ Distribution: PARTITIONED │ maySkipOutputDuplicates = true ├─ RemoteSource[sourceFragmentIds = [3]] │ Layout: [expr_539:varchar(7), expr_538:varchar(12), utm_medium:varchar, utm_term:varchar, expr_1317:varchar, expr_533:unknown, expr_532:varchar(6), id_4:integer, expr_531:date, expr_537:varchar, user_activity_type:varchar, expr_535:varchar(3), expr_534:varchar, utm_source:varchar] └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=varchar, name=expr_1318]]] │ Layout: [expr_1316:varchar(14), expr_1318:varchar, id_610:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [52]] Layout: [expr_1316:varchar(14), expr_1318:varchar, id_610:integer] Fragment 3 [HASH] Output layout: [expr_539, expr_538, utm_medium, utm_term, expr_1317, expr_533, expr_532, id_4, expr_531, expr_537, user_activity_type, expr_535, expr_534, utm_source] Output partitioning: HASH [expr_1317] Project[] │ Layout: [expr_539:varchar(7), expr_538:varchar(12), utm_medium:varchar, utm_term:varchar, expr_1317:varchar, expr_533:unknown, expr_532:varchar(6), id_4:integer, expr_531:date, expr_537:varchar, user_activity_type:varchar, expr_535:varchar(3), expr_534:varchar, utm_source:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ expr_539 := (CASE WHEN (expr_192 = varchar 'hub') THEN varchar(7) 'hub' WHEN (expr_192 IN varchar 'Olx', varchar 'CarDekho', varchar 'CarTrade') THEN varchar(7) 'Offline' ELSE varchar(7) 'Online' END) │ expr_1317 := CAST(id_4 AS varchar) └─ Project[] │ Layout: [id_4:integer, user_activity_type:varchar, expr_531:date, expr_532:varchar(6), expr_533:unknown, expr_192:varchar, expr_534:varchar, utm_source:varchar, utm_medium:varchar, utm_term:varchar, expr_535:varchar(3), expr_537:varchar, expr_538:varchar(12)] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ Aggregate[keys = [id, id_4, user_activity_type, expr_530, expr_531, no_of_testdrives, display_name_471, expr_532, expr_533, expr_192, expr_534, utm_source, utm_medium, utm_term, expr_535, expr_536, registration_no, row_number_529, expr_537, expr_538]] │ Layout: [id:integer, id_4:integer, user_activity_type:varchar, expr_530:bigint, expr_531:date, no_of_testdrives:integer, display_name_471:varchar, expr_532:varchar(6), expr_533:unknown, expr_192:varchar, expr_534:varchar, utm_source:varchar, utm_medium:varchar, utm_term:varchar, expr_535:varchar(3), expr_536:varchar(18), registration_no:varchar, row_number_529:bigint, expr_537:varchar, expr_538:varchar(12)] │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} └─ FilterProject[filterPredicate = (CAST((visit_start_time + interval day to second '0 05:30:00.000') AS date) >= date '2024-03-12')] │ Layout: [row_number_529:bigint, expr_538:varchar(12), utm_medium:varchar, display_name_471:varchar, registration_no:varchar, utm_term:varchar, expr_192:varchar, no_of_testdrives:integer, expr_533:unknown, expr_532:varchar(6), id_4:integer, expr_531:date, id:integer, expr_530:bigint, expr_537:varchar, expr_536:varchar(18), user_activity_type:varchar, expr_535:varchar(3), utm_source:varchar, expr_534:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B}/{rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ expr_538 := (CASE WHEN (NOT (full_name IS NULL)) THEN varchar(12) 'Assigned' ELSE varchar(12) 'Not_Assigned' END) │ expr_533 := null::unknown │ expr_532 := (CASE WHEN system.builtin.$like(platform_source, LikePattern '[%app%]') THEN varchar(6) 'App' WHEN system.builtin.$like(platform_source, LikePattern '[%web%]') THEN varchar(6) 'Web' WHEN system.builtin.$like(platform_source, LikePattern '[%mweb%]') THEN varchar(6) 'Web' ELSE varchar(6) 'Others' END) │ expr_531 := CAST((visit_start_time + interval day to second '0 05:30:00.000') AS date) │ expr_530 := system.builtin.day(CAST((visit_start_time + interval day to second '0 05:30:00.000') AS date)) │ expr_537 := (CASE WHEN system.builtin.$like(display_name_471, LikePattern '[%Delhi%]') THEN varchar 'NCR' WHEN system.builtin.$like(display_name_471, LikePattern '[%Bangalore%]') THEN varchar 'Bangalore' WHEN system.builtin.$like(display_name_471, LikePattern '[%Hyderabad%]') THEN varchar 'Hyderabad' WHEN system.builtin.$like(display_name_471, LikePattern '[%Gurgaon%]') THEN varchar 'NCR' WHEN system.builtin.$like(display_name_471, LikePattern '[%Punee%]') THEN varchar 'Pune' WHEN system.builtin.$like(display_name_471, LikePattern '[%Mumbai%]') THEN varchar 'Mumbai' WHEN system.builtin.$like(display_name_471, LikePattern '[%Delhi/Delhi NCR%]') THEN varchar 'NCR' WHEN system.builtin.$like(display_name_471, LikePattern '[%Ahmedabad%]') THEN varchar 'Ahmedabad' WHEN system.builtin.$like(display_name_471, LikePattern '[%Noida%]') THEN varchar 'NCR' WHEN system.builtin.$like(display_name_471, LikePattern '[%Chennai%]') THEN varchar 'Chennai' WHEN system.builtin.$like(display_name_471, LikePattern '[%Lucknow%]') THEN varchar 'Lucknow' WHEN system.builtin.$like(display_name_471, LikePattern '[%Kolkata%]') THEN varchar 'Kolkata' WHEN system.builtin.$like(display_name_471, LikePattern '[%Ghaziabad%]') THEN varchar 'NCR' WHEN system.builtin.$like(display_name_471, LikePattern '[%Faridabad%]') THEN varchar 'NCR' WHEN system.builtin.$like(display_name_471, LikePattern '[%Jaipur%]') THEN varchar 'Jaipur' WHEN system.builtin.$like(display_name_471, LikePattern '[%Indore%]') THEN varchar 'Indore' WHEN system.builtin.$like(display_name_471, LikePattern '[%Mysore%]') THEN varchar 'Bangalore' WHEN system.builtin.$like(display_name_471, LikePattern '[%Coimbatore%]') THEN varchar 'Coimbatore' WHEN system.builtin.$like(display_name_471, LikePattern '[%Chandigarh%]') THEN varchar 'Chandigarh' WHEN system.builtin.$like(display_name_471, LikePattern '[%Rewari%]') THEN varchar 'NCR' WHEN system.builtin.$like(display_name_471, LikePattern '[%Ambala%]') THEN varchar 'Chandigarh' WHEN system.builtin.$like(display_name_471, LikePattern '[%Hubli%]') THEN varchar 'Bangalore' WHEN system.builtin.$like(display_name_471, LikePattern '[%Panipat%]') THEN varchar 'NCR' WHEN system.builtin.$like(display_name_471, LikePattern '[%Greater Noida%]') THEN varchar 'NCR' WHEN system.builtin.$like(display_name_471, LikePattern '[%Rohtak%]') THEN varchar 'NCR' WHEN system.builtin.$like(display_name_471, LikePattern '[%Meerut%]') THEN varchar 'NCR' WHEN system.builtin.$like(display_name_471, LikePattern '[%Karnal%]') THEN varchar 'NCR' WHEN system.builtin.$like(display_name_471, LikePattern '[%Sonipat%]') THEN varchar 'NCR' WHEN system.builtin.$like(display_name_471, LikePattern '[%Kanpur%]') THEN varchar 'Lucknow' WHEN system.builtin.$like(display_name_471, LikePattern '[%Mangalore%]') THEN varchar 'Bangalore' WHEN system.builtin.$like(display_name_471, LikePattern '[%Surat%]') THEN varchar 'Surat' WHEN system.builtin.$like(display_name_471, LikePattern '[%Aligarh%]') THEN varchar 'NCR' WHEN system.builtin.$like(display_name_471, LikePattern '[%Belgaum%]') THEN varchar 'Bangalore' WHEN system.builtin.$like(display_name_471, LikePattern '[%Hassan%]') THEN varchar 'Bangalore' WHEN system.builtin.$like(display_name_471, LikePattern '[%Jammu%]') THEN varchar 'NCR' WHEN system.builtin.$like(display_name_471, LikePattern '[%Jhajjar%]') THEN varchar 'NCR' WHEN system.builtin.$like(display_name_471, LikePattern '[%Agra%]') THEN varchar 'NCR' WHEN system.builtin.$like(display_name_471, LikePattern '[%Bhiwadi%]') THEN varchar 'Jaipur' WHEN system.builtin.$like(display_name_471, LikePattern '[%Kolar%]') THEN varchar 'Bangalore' WHEN system.builtin.$like(display_name_471, LikePattern '[%Gulbarga%]') THEN varchar 'Bangalore' WHEN system.builtin.$like(display_name_471, LikePattern '[%Warangal%]') THEN varchar 'Hyderabad' WHEN system.builtin.$like(display_name_471, LikePattern '[%Raichur%]') THEN varchar 'Bangalore' WHEN system.builtin.$like(display_name_471, LikePattern '[%Alwar%]') THEN varchar 'NCR' WHEN system.builtin.$like(display_name_471, LikePattern '[%Nashik%]') THEN varchar 'Pune' WHEN system.builtin.$like(display_name_471, LikePattern '[%Bahadurgarh%]') THEN varchar 'NCR' WHEN system.builtin.$like(display_name_471, LikePattern '[%Mathura%]') THEN varchar 'NCR' WHEN system.builtin.$like(display_name_471, LikePattern '[%Sirsa%]') THEN varchar 'Chandigarh' WHEN system.builtin.$like(display_name_471, LikePattern '[%Thane%]') THEN varchar 'Mumbai' WHEN system.builtin.$like(display_name_471, LikePattern '[%Nagpur%]') THEN varchar 'Pune' WHEN system.builtin.$like(display_name_471, LikePattern '[%Moradabad%]') THEN varchar 'Lucknow' WHEN system.builtin.$like(display_name_471, LikePattern '[%Karimnagar%]') THEN varchar 'Hyderabad' WHEN system.builtin.$like(display_name_471, LikePattern '[%Amritsar%]') THEN varchar 'Chandigarh' WHEN system.builtin.$like(display_name_471, LikePattern '[%Patna%]') THEN varchar 'Lucknow' WHEN system.builtin.$like(display_name_471, LikePattern '[%Bagalkot%]') THEN varchar 'Bangalore' WHEN system.builtin.$like(display_name_471, LikePattern '[%Kochi%]') THEN varchar 'Kochi' WHEN system.builtin.$like(display_name_471, LikePattern '[%Jhansi%]') THEN varchar 'Lucknow' WHEN system.builtin.$like(display_name_471, LikePattern '[%Nizamabad%]') THEN varchar 'Hyderabad' WHEN system.builtin.$like(display_name_471, LikePattern '[%Bareilly%]') THEN varchar 'Lucknow' WHEN system.builtin.$like(display_name_471, LikePattern '[%Saharanpur%]') THEN varchar 'Lucknow' WHEN system.builtin.$like(display_name_471, LikePattern '[%Navi Mumbai%]') THEN varchar 'Mumbai' WHEN system.builtin.$like(display_name_471, LikePattern '[%Jodhpur%]') THEN varchar 'Jaipur' WHEN system.builtin.$like(display_name_471, LikePattern '[%Gwalior%]') THEN varchar 'Indore' WHEN system.builtin.$like(display_name_471, LikePattern '[%Hapur%]') THEN varchar 'NCR' WHEN system.builtin.$like(display_name_471, LikePattern '[%Bhopal%]') THEN varchar 'Indore' WHEN system.builtin.$like(display_name_471, LikePattern '[%Dehradun%]') THEN varchar 'NCR' WHEN system.builtin.$like(display_name_471, LikePattern '[%Kurukshetra%]') THEN varchar 'Chandigarh' WHEN system.builtin.$like(display_name_471, LikePattern '[%Ahmednagar%]') THEN varchar 'Pune' WHEN system.builtin.$like(display_name_471, LikePattern '[%Mandya%]') THEN varchar 'Bangalore' WHEN system.builtin.$like(display_name_471, LikePattern '[%Aurangabad%]') THEN varchar 'Pune' WHEN system.builtin.$like(display_name_471, LikePattern '[%Jalandhar%]') THEN varchar 'Chandigarh' WHEN system.builtin.$like(display_name_471, LikePattern '[%Gorakhpur%]') THEN varchar 'Lucknow' WHEN system.builtin.$like(display_name_471, LikePattern '[%Khammam%]') THEN varchar 'Hyderabad' WHEN system.builtin.$like(display_name_471, LikePattern '[%Muzaffarnagar%]') THEN varchar 'NCR' WHEN system.builtin.$like(display_name_471, LikePattern '[%Rajkot%]') THEN varchar 'Ahmedabad' WHEN system.builtin.$like(display_name_471, LikePattern '[%Varanasi%]') THEN varchar 'Lucknow' WHEN system.builtin.$like(display_name_471, LikePattern '[%Hosur%]') THEN varchar 'Coimbatore' WHEN system.builtin.$like(display_name_471, LikePattern '[%Allahabad%]') THEN varchar 'Lucknow' WHEN system.builtin.$like(display_name_471, LikePattern '[%Bathinda%]') THEN varchar 'Chandigarh' WHEN system.builtin.$like(display_name_471, LikePattern '[%Solapur%]') THEN varchar 'Pune' WHEN system.builtin.$like(display_name_471, LikePattern '[%Vadodara%]') THEN varchar 'Ahmedabad' WHEN system.builtin.$like(display_name_471, LikePattern '[%tumkur%]') THEN varchar 'Bangalore' WHEN system.builtin.$like(display_name_471, LikePattern '[%tumakuru%]') THEN varchar 'Bangalore' WHEN system.builtin.$like(display_name_471, LikePattern '[%shimoga%]') THEN varchar 'Bangalore' WHEN system.builtin.$like(display_name_471, LikePattern '[%Shivamogga%]') THEN varchar 'Bangalore' WHEN system.builtin.$like(display_name_471, LikePattern '[%Navi Mumbai%]') THEN varchar 'Mumbai' WHEN system.builtin.$like(display_name_471, LikePattern '[%Navsari%]') THEN varchar 'Ahmedabad' WHEN system.builtin.$like(display_name_471, LikePattern '[%Pune%]') THEN varchar 'Pune' WHEN system.builtin.$like(display_name_471, LikePattern '[%sangli%]') THEN varchar 'Pune' WHEN system.builtin.$like(display_name_471, LikePattern '[%Bhavnagar%]') THEN varchar 'Ahmedabad' WHEN system.builtin.$like(display_name_471, LikePattern '[%Surat%]') THEN varchar 'Surat' ELSE display_name_471 END) │ expr_536 := (CASE WHEN (tag_status = varchar 'available') THEN varchar(18) 'Available' WHEN (tag_status = varchar 'available-&-booked') THEN varchar(18) 'Booked' WHEN (tag_status = varchar 'available-&-in-refurb') THEN varchar(18) 'In refurb' WHEN (tag_status = varchar 'available-&-booked-&-in-refurb') THEN varchar(18) 'Booked & In Refurb' WHEN (tag_status = varchar 'booked') THEN varchar(18) 'Booked' WHEN (tag_status = varchar 'in-refurb') THEN varchar(18) 'In Refurb' WHEN (tag_status = varchar 'upcoming-supply') THEN varchar(18) 'Upcoming Supply' WHEN (tag_status = varchar 'sold') THEN varchar(18) 'Sold' END) │ expr_535 := (CASE WHEN (at_home = integer '1') THEN varchar(3) 'HTD' ELSE varchar(3) 'HV' END) │ expr_534 := (CASE WHEN (NOT (cta_slug IS NULL)) THEN cta_slug ELSE (CASE WHEN (sub_source = varchar 'neutral_page') THEN varchar 'neutral_page' ELSE expr_192 END) END) └─ TopNRanking[partitionBy = [id_4], orderBy = [visit_start_time ASC NULLS LAST], limit = 1] │ Layout: [at_home:integer, id_4:integer, id:integer, no_of_testdrives:integer, visit_start_time:timestamp(6) with time zone, platform_source:varchar, sub_source:varchar, full_name:varchar, expr_192:varchar, cta_slug:varchar, utm_medium:varchar, utm_source:varchar, utm_term:varchar, user_activity_type:varchar, display_name_471:varchar, tag_status:varchar, registration_no:varchar, row_number_529:bigint] │ row_number_529 := ROW_NUMBER └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=integer, name=id_4]]] │ Layout: [at_home:integer, id_4:integer, id:integer, no_of_testdrives:integer, visit_start_time:timestamp(6) with time zone, platform_source:varchar, sub_source:varchar, full_name:varchar, expr_192:varchar, cta_slug:varchar, utm_medium:varchar, utm_source:varchar, utm_term:varchar, user_activity_type:varchar, display_name_471:varchar, tag_status:varchar, registration_no:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [4]] Layout: [at_home:integer, id_4:integer, id:integer, no_of_testdrives:integer, visit_start_time:timestamp(6) with time zone, platform_source:varchar, sub_source:varchar, full_name:varchar, expr_192:varchar, cta_slug:varchar, utm_medium:varchar, utm_source:varchar, utm_term:varchar, user_activity_type:varchar, display_name_471:varchar, tag_status:varchar, registration_no:varchar] Fragment 4 [HASH] Output layout: [at_home, id_4, id, no_of_testdrives, visit_start_time, platform_source, sub_source, full_name, expr_192, cta_slug, utm_medium, utm_source, utm_term, user_activity_type, display_name_471, tag_status, registration_no] Output partitioning: HASH [id_4] TopNRanking[partitionBy = [id_4], orderBy = [visit_start_time ASC NULLS LAST], limit = 1] │ Layout: [at_home:integer, id_4:integer, id:integer, no_of_testdrives:integer, visit_start_time:timestamp(6) with time zone, platform_source:varchar, sub_source:varchar, full_name:varchar, expr_192:varchar, cta_slug:varchar, utm_medium:varchar, utm_source:varchar, utm_term:varchar, user_activity_type:varchar, display_name_471:varchar, tag_status:varchar, registration_no:varchar] │ row_number_529 := ROW_NUMBER └─ InnerJoin[criteria = (status_id = id_524), distribution = REPLICATED] │ Layout: [at_home:integer, id_4:integer, id:integer, no_of_testdrives:integer, visit_start_time:timestamp(6) with time zone, platform_source:varchar, sub_source:varchar, full_name:varchar, expr_192:varchar, cta_slug:varchar, utm_medium:varchar, utm_source:varchar, utm_term:varchar, user_activity_type:varchar, display_name_471:varchar, tag_status:varchar, registration_no:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} │ Distribution: REPLICATED │ dynamicFilterAssignments = {id_524 -> #df_16594} ├─ LeftJoin[criteria = (profile_id = id_513), distribution = PARTITIONED] │ │ Layout: [at_home:integer, id_4:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone, platform_source:varchar, sub_source:varchar, full_name:varchar, expr_192:varchar, cta_slug:varchar, utm_medium:varchar, utm_source:varchar, utm_term:varchar, user_activity_type:varchar, display_name_471:varchar, tag_status:varchar, registration_no:varchar] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 513.68MB, network: 0B} │ │ Distribution: PARTITIONED │ ├─ RemoteSource[sourceFragmentIds = [5]] │ │ Layout: [at_home:integer, id_4:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone, platform_source:varchar, sub_source:varchar, full_name:varchar, expr_192:varchar, cta_slug:varchar, utm_medium:varchar, utm_source:varchar, utm_term:varchar, user_activity_type:varchar, display_name_471:varchar, profile_id:integer, tag_status:varchar] │ └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=integer, name=id_513]]] │ │ Layout: [id_513:integer, registration_no:varchar] │ │ Estimates: {rows: 26793658 (513.68MB), cpu: 513.68M, memory: 0B, network: 0B} │ └─ RemoteSource[sourceFragmentIds = [50]] │ Layout: [id_513:integer, registration_no:varchar] └─ LocalExchange[partitioning = SINGLE] │ Layout: [id_524:integer] │ Estimates: {rows: ? (?), cpu: 0, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [51]] Layout: [id_524:integer] Fragment 5 [HASH] Output layout: [at_home, id_4, id, no_of_testdrives, status_id, visit_start_time, platform_source, sub_source, full_name, expr_192, cta_slug, utm_medium, utm_source, utm_term, user_activity_type, display_name_471, profile_id, tag_status] Output partitioning: HASH [profile_id] LeftJoin[criteria = (sell_lead_id_483 = id_495), distribution = PARTITIONED] │ Layout: [at_home:integer, id_4:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone, platform_source:varchar, sub_source:varchar, full_name:varchar, expr_192:varchar, cta_slug:varchar, utm_medium:varchar, utm_source:varchar, utm_term:varchar, user_activity_type:varchar, display_name_471:varchar, profile_id:integer, tag_status:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 210.65MB, network: 0B} │ Distribution: PARTITIONED ├─ RemoteSource[sourceFragmentIds = [6]] │ Layout: [at_home:integer, id_4:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone, platform_source:varchar, sub_source:varchar, full_name:varchar, expr_192:varchar, cta_slug:varchar, utm_medium:varchar, utm_source:varchar, utm_term:varchar, user_activity_type:varchar, display_name_471:varchar, sell_lead_id_483:integer] └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=integer, name=id_495]]] │ Layout: [id_495:integer, profile_id:integer, tag_status:varchar] │ Estimates: {rows: 14393538 (210.65MB), cpu: 210.65M, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [49]] Layout: [id_495:integer, profile_id:integer, tag_status:varchar] Fragment 6 [HASH] Output layout: [at_home, id_4, id, no_of_testdrives, status_id, visit_start_time, platform_source, sub_source, full_name, expr_192, cta_slug, utm_medium, utm_source, utm_term, user_activity_type, display_name_471, sell_lead_id_483] Output partitioning: HASH [sell_lead_id_483] LeftJoin[criteria = (id = visit_id), distribution = REPLICATED] │ Layout: [at_home:integer, id_4:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone, platform_source:varchar, sub_source:varchar, full_name:varchar, expr_192:varchar, cta_slug:varchar, utm_medium:varchar, utm_source:varchar, utm_term:varchar, user_activity_type:varchar, display_name_471:varchar, sell_lead_id_483:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: 534.87MB, network: 0B} │ Distribution: REPLICATED ├─ LeftJoin[criteria = (city_id = id_472), distribution = REPLICATED] │ │ Layout: [at_home:integer, id_4:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone, platform_source:varchar, sub_source:varchar, full_name:varchar, expr_192:varchar, cta_slug:varchar, utm_medium:varchar, utm_source:varchar, utm_term:varchar, user_activity_type:varchar, display_name_471:varchar] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 275.71kB, network: 0B} │ │ Distribution: REPLICATED │ ├─ LeftJoin[criteria = (hub_id = id_464), distribution = REPLICATED] │ │ │ Layout: [at_home:integer, id_4:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone, city_id:integer, platform_source:varchar, sub_source:varchar, full_name:varchar, expr_192:varchar, cta_slug:varchar, utm_medium:varchar, utm_source:varchar, utm_term:varchar, user_activity_type:varchar] │ │ │ Estimates: {rows: ? (?), cpu: ?, memory: 12.39kB, network: 0B} │ │ │ Distribution: REPLICATED │ │ ├─ LeftJoin[criteria = (id_449 = marketing_attribution_id_458), distribution = PARTITIONED] │ │ │ │ Layout: [at_home:integer, id_4:integer, hub_id:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone, city_id:integer, platform_source:varchar, sub_source:varchar, full_name:varchar, expr_192:varchar, cta_slug:varchar, utm_medium:varchar, utm_source:varchar, utm_term:varchar, user_activity_type:varchar] │ │ │ │ Estimates: {rows: ? (?), cpu: ?, memory: 117.48MB, network: 0B} │ │ │ │ Distribution: PARTITIONED │ │ │ ├─ RemoteSource[sourceFragmentIds = [7]] │ │ │ │ Layout: [at_home:integer, id_4:integer, hub_id:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone, city_id:integer, platform_source:varchar, sub_source:varchar, full_name:varchar, expr_192:varchar, cta_slug:varchar, id_449:integer, utm_medium:varchar, utm_source:varchar, utm_term:varchar] │ │ │ └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=integer, name=marketing_attribution_id_458]]] │ │ │ │ Layout: [marketing_attribution_id_458:integer, user_activity_type:varchar] │ │ │ │ Estimates: {rows: 12125080 (117.48MB), cpu: 117.48M, memory: 0B, network: 0B} │ │ │ └─ RemoteSource[sourceFragmentIds = [45]] │ │ │ Layout: [marketing_attribution_id_458:integer, user_activity_type:varchar] │ │ └─ LocalExchange[partitioning = SINGLE] │ │ │ Layout: [id_464:integer] │ │ │ Estimates: {rows: 141 (705B), cpu: 0, memory: 0B, network: 0B} │ │ └─ RemoteSource[sourceFragmentIds = [46]] │ │ Layout: [id_464:integer] │ └─ LocalExchange[partitioning = SINGLE] │ │ Layout: [display_name_471:varchar, id_472:integer] │ │ Estimates: {rows: 454 (15.32kB), cpu: 0, memory: 0B, network: 0B} │ └─ RemoteSource[sourceFragmentIds = [47]] │ Layout: [display_name_471:varchar, id_472:integer] └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=integer, name=visit_id]]] │ Layout: [sell_lead_id_483:integer, visit_id:integer] │ Estimates: {rows: 3116766 (29.72MB), cpu: 29.72M, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [48]] Layout: [sell_lead_id_483:integer, visit_id:integer] Fragment 7 [HASH] Output layout: [at_home, id_4, hub_id, id, no_of_testdrives, status_id, visit_start_time, city_id, platform_source, sub_source, full_name, expr_192, cta_slug, id_449, utm_medium, utm_source, utm_term] Output partitioning: HASH [id_449] LeftJoin[criteria = (expr_446 = id_449), distribution = PARTITIONED] │ Layout: [at_home:integer, id_4:integer, hub_id:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone, city_id:integer, platform_source:varchar, sub_source:varchar, full_name:varchar, expr_192:varchar, cta_slug:varchar, id_449:integer, utm_medium:varchar, utm_source:varchar, utm_term:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 5.05GB, network: 0B} │ Distribution: PARTITIONED ├─ RemoteSource[sourceFragmentIds = [8]] │ Layout: [at_home:integer, id_4:integer, hub_id:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone, city_id:integer, platform_source:varchar, sub_source:varchar, full_name:varchar, expr_192:varchar, cta_slug:varchar, expr_446:integer] └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=integer, name=id_449]]] │ Layout: [id_449:integer, utm_medium:varchar, utm_source:varchar, utm_term:varchar] │ Estimates: {rows: 196944231 (5.05GB), cpu: 5.05G, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [44]] Layout: [id_449:integer, utm_medium:varchar, utm_source:varchar, utm_term:varchar] Fragment 8 [HASH] Output layout: [at_home, id_4, hub_id, id, no_of_testdrives, status_id, visit_start_time, city_id, platform_source, sub_source, full_name, expr_192, cta_slug, expr_446] Output partitioning: HASH [expr_446] LeftJoin[criteria = (id_4 = id_211), distribution = PARTITIONED] │ Layout: [at_home:integer, id_4:integer, hub_id:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone, city_id:integer, platform_source:varchar, sub_source:varchar, full_name:varchar, expr_192:varchar, cta_slug:varchar, expr_446:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} │ Distribution: PARTITIONED ├─ LeftJoin[criteria = (id_4 = id_53), distribution = PARTITIONED] │ │ Layout: [at_home:integer, id_4:integer, hub_id:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone, city_id:integer, platform_source:varchar, sub_source:varchar, full_name:varchar, expr_192:varchar] │ │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} │ │ Distribution: PARTITIONED │ ├─ RemoteSource[sourceFragmentIds = [9]] │ │ Layout: [at_home:integer, id_4:integer, hub_id:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone, city_id:integer, platform_source:varchar, sub_source:varchar, full_name:varchar] │ └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=integer, name=id_53]]] │ │ Layout: [expr_192:varchar, id_53:integer] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ └─ Project[] │ │ Layout: [expr_192:varchar, id_53:integer] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ │ expr_192 := (CASE WHEN (expr = varchar 'www.olx.in') THEN varchar 'Olx' WHEN (expr = varchar 'www.cardekho.com') THEN varchar 'CarDekho' WHEN (expr = varchar 'www.cartrade.com') THEN varchar 'CarTrade' ELSE expr END) │ └─ Project[] │ │ Layout: [id_53:integer, expr:varchar] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ │ expr := (CASE WHEN (source_object_type_id_71 = integer '321') THEN display_name_183 WHEN ((source_object_type_id_71 = integer '246') AND (url_189 = varchar 'Direct')) THEN varchar 'direct' WHEN (source_object_type_id_71 = integer '319') THEN display_name_100 WHEN (source_object_type_id_71 = integer '322') THEN display_name_100 ELSE model END) │ └─ LeftJoin[criteria = (source_object_id_70 = id_188), filter = (source_object_type_id_71 = integer '246'), distribution = REPLICATED] │ │ Layout: [id_53:integer, source_object_type_id_71:integer, model:varchar, display_name_100:varchar, display_name_183:varchar, url_189:varchar] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 19.28MB, network: 0B} │ │ Distribution: REPLICATED │ ├─ LeftJoin[criteria = (id_53 = id_122), distribution = PARTITIONED] │ │ │ Layout: [id_53:integer, source_object_id_70:integer, source_object_type_id_71:integer, model:varchar, display_name_100:varchar, display_name_183:varchar] │ │ │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} │ │ │ Distribution: PARTITIONED │ │ ├─ RemoteSource[sourceFragmentIds = [18]] │ │ │ Layout: [id_53:integer, source_object_id_70:integer, source_object_type_id_71:integer, model:varchar, display_name_100:varchar] │ │ └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=integer, name=id_122]]] │ │ │ Layout: [id_122:integer, display_name_183:varchar] │ │ │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ │ └─ RemoteSource[sourceFragmentIds = [24]] │ │ Layout: [id_122:integer, display_name_183:varchar] │ └─ LocalExchange[partitioning = SINGLE] │ │ Layout: [id_188:integer, url_189:varchar] │ │ Estimates: {rows: 9042 (1.07MB), cpu: 0, memory: 0B, network: 0B} │ └─ RemoteSource[sourceFragmentIds = [29]] │ Layout: [id_188:integer, url_189:varchar] └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=integer, name=id_211]]] │ Layout: [id_211:integer, cta_slug:varchar, expr_446:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ Project[] │ Layout: [id_211:integer, cta_slug:varchar, expr_446:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ expr_446 := (CASE WHEN (id_211 = id_334) THEN min ELSE marketing_attribution_id END) └─ LeftJoin[criteria = (id_211 = id_334), distribution = PARTITIONED] │ Layout: [id_211:integer, marketing_attribution_id:integer, cta_slug:varchar, id_334:integer, min:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} │ Distribution: PARTITIONED ├─ RemoteSource[sourceFragmentIds = [30]] │ Layout: [id_211:integer, marketing_attribution_id:integer, cta_slug:varchar] └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=integer, name=id_334]]] │ Layout: [id_334:integer, min:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [37]] Layout: [id_334:integer, min:integer] Fragment 9 [HASH] Output layout: [at_home, id_4, hub_id, id, no_of_testdrives, status_id, visit_start_time, city_id, platform_source, sub_source, full_name] Output partitioning: HASH [id_4] LeftJoin[criteria = (account_id = account_id_29), distribution = PARTITIONED] │ Layout: [at_home:integer, id_4:integer, hub_id:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone, city_id:integer, platform_source:varchar, sub_source:varchar, full_name:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 582.75MB, network: 0B} │ Distribution: PARTITIONED ├─ RemoteSource[sourceFragmentIds = [10]] │ Layout: [at_home:integer, id_4:integer, hub_id:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone, account_id:integer, city_id:integer, platform_source:varchar, sub_source:varchar, full_name:varchar] └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=integer, name=account_id_29]]] │ Layout: [account_id_29:integer] │ Estimates: {rows: 128100977 (582.75MB), cpu: 582.75M, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [17]] Layout: [account_id_29:integer] Fragment 10 [HASH] Output layout: [at_home, id_4, hub_id, id, no_of_testdrives, status_id, visit_start_time, account_id, city_id, platform_source, sub_source, full_name] Output partitioning: HASH [account_id] LeftJoin[criteria = (assigned_to_id_9 = id_23), distribution = PARTITIONED] │ Layout: [at_home:integer, id_4:integer, hub_id:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone, account_id:integer, city_id:integer, platform_source:varchar, sub_source:varchar, full_name:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 438.19MB, network: 0B} │ Distribution: PARTITIONED ├─ RemoteSource[sourceFragmentIds = [11]] │ Layout: [at_home:integer, id_4:integer, hub_id:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone, account_id:integer, city_id:integer, platform_source:varchar, sub_source:varchar, assigned_to_id_9:integer] └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=integer, name=id_23]]] │ Layout: [full_name:varchar, id_23:integer] │ Estimates: {rows: 17988382 (438.19MB), cpu: 438.19M, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [16]] Layout: [full_name:varchar, id_23:integer] Fragment 11 [HASH] Output layout: [at_home, id_4, hub_id, id, no_of_testdrives, status_id, visit_start_time, account_id, city_id, platform_source, sub_source, assigned_to_id_9] Output partitioning: HASH [assigned_to_id_9] LeftJoin[criteria = (id_4 = context_id_10), distribution = PARTITIONED] │ Layout: [account_id:integer, city_id:integer, platform_source:varchar, sub_source:varchar, id_4:integer, at_home:integer, hub_id:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone, assigned_to_id_9:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} │ Distribution: PARTITIONED ├─ InnerJoin[criteria = (id_4 = context_id), distribution = PARTITIONED] │ │ Layout: [account_id:integer, city_id:integer, id_4:integer, platform_source:varchar, sub_source:varchar, at_home:integer, hub_id:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 19.92MB, network: 0B} │ │ Distribution: PARTITIONED │ │ dynamicFilterAssignments = {context_id -> #df_16595} │ ├─ RemoteSource[sourceFragmentIds = [12]] │ │ Layout: [account_id:integer, city_id:integer, id_4:integer, platform_source:varchar, sub_source:varchar] │ └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=integer, name=context_id]]] │ │ Layout: [at_home:integer, context_id:integer, hub_id:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone] │ │ Estimates: {rows: 586333 (19.92MB), cpu: 19.92M, memory: 0B, network: 0B} │ └─ RemoteSource[sourceFragmentIds = [13]] │ Layout: [at_home:integer, context_id:integer, hub_id:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone] └─ FilterProject[filterPredicate = (row_number = bigint '1')] │ Layout: [assigned_to_id_9:integer, context_id_10:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B}/{rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ Project[] │ Layout: [assigned_to_id_9:integer, context_id_10:integer, row_number:bigint] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ TopNRanking[partitionBy = [context_id_10], orderBy = [created_time DESC NULLS LAST], limit = 1] │ Layout: [assigned_to_id_9:integer, context_id_10:integer, created_time:timestamp(6) with time zone, row_number:bigint] │ row_number := ROW_NUMBER └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=integer, name=context_id_10]]] │ Layout: [assigned_to_id_9:integer, context_id_10:integer, created_time:timestamp(6) with time zone] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [14]] Layout: [assigned_to_id_9:integer, context_id_10:integer, created_time:timestamp(6) with time zone] Fragment 12 [SOURCE] Output layout: [account_id, city_id, id_4, platform_source, sub_source] Output partitioning: HASH [id_4] ScanFilterProject[table = iceberg:sp_web.buy_lead_buylead$data@1299828741364571249, filterPredicate = (category = varchar 'assured'), dynamicFilters = {id_4 = #df_16595}] Layout: [account_id:integer, city_id:integer, id_4:integer, platform_source:varchar, sub_source:varchar] Estimates: {rows: 12700031 (334.11MB), cpu: 400.56M, memory: 0B, network: 0B}/{rows: 6350016 (167.05MB), cpu: 400.56M, memory: 0B, network: 0B}/{rows: 6350016 (167.05MB), cpu: 167.05M, memory: 0B, network: 0B} id_4 := 19:id:integer platform_source := 28:platform_source:varchar sub_source := 39:sub_source:varchar account_id := 1:account_id:integer category := 8:category:varchar city_id := 9:city_id:integer Fragment 13 [SOURCE] Output layout: [at_home, context_id, hub_id, id, no_of_testdrives, status_id, visit_start_time] Output partitioning: HASH [context_id] ScanFilter[table = iceberg:sp_web.visits_visit$data@918499440402197125, filterPredicate = (CAST((visit_start_time + interval day to second '0 05:30:00.000') AS date) >= date '2024-01-01'), dynamicFilters = {status_id = #df_16594}] Layout: [at_home:integer, context_id:integer, hub_id:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone] Estimates: {rows: 2977093 (101.12MB), cpu: 101.12M, memory: 0B, network: 0B}/{rows: 586333 (19.92MB), cpu: 101.12M, memory: 0B, network: 0B} at_home := 2:at_home:integer hub_id := 24:hub_id:integer status_id := 36:status_id:integer no_of_testdrives := 28:no_of_testdrives:integer context_id := 12:context_id:integer id := 25:id:integer visit_start_time := 48:visit_start_time:timestamp(6) with time zone Fragment 14 [SOURCE] Output layout: [assigned_to_id_9, context_id_10, created_time] Output partitioning: HASH [context_id_10] TopNRanking[partitionBy = [context_id_10], orderBy = [created_time DESC NULLS LAST], limit = 1] │ Layout: [assigned_to_id_9:integer, context_id_10:integer, created_time:timestamp(6) with time zone] │ row_number := ROW_NUMBER └─ InnerJoin[criteria = (assigned_to_id_9 = user_id_19), distribution = REPLICATED] │ Layout: [assigned_to_id_9:integer, context_id_10:integer, created_time:timestamp(6) with time zone] │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} │ Distribution: REPLICATED │ dynamicFilterAssignments = {user_id_19 -> #df_16601} ├─ ScanFilter[table = iceberg:sp_web.workflow_usertask$data@2993060954803322895, dynamicFilters = {assigned_to_id_9 = #df_16601}] │ Layout: [assigned_to_id_9:integer, context_id_10:integer, created_time:timestamp(6) with time zone] │ Estimates: {rows: 169318201 (3.56GB), cpu: 3.56G, memory: 0B, network: 0B}/{rows: 169318201 (3.56GB), cpu: 3.56G, memory: 0B, network: 0B} │ created_time := 5:created_time:timestamp(6) with time zone │ context_id_10 := 3:context_id:integer │ assigned_to_id_9 := 2:assigned_to_id:integer └─ LocalExchange[partitioning = SINGLE] │ Layout: [user_id_19:integer] │ Estimates: {rows: ? (?), cpu: 0, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [15]] Layout: [user_id_19:integer] Fragment 15 [SOURCE] Output layout: [user_id_19] Output partitioning: BROADCAST [] ScanFilterProject[table = iceberg:sp_web.spinny_auth_user_groups$data@4640214938704829124, filterPredicate = (group_id IN integer '132', integer '206')] Layout: [user_id_19:integer] Estimates: {rows: 30103 (146.99kB), cpu: 293.97k, memory: 0B, network: 0B}/{rows: ? (?), cpu: 293.97k, memory: 0B, network: 0B}/{rows: ? (?), cpu: ?, memory: 0B, network: 0B} group_id := 1:group_id:integer user_id_19 := 4:user_id:integer Fragment 16 [SOURCE] Output layout: [full_name, id_23] Output partitioning: HASH [id_23] TableScan[table = iceberg:sp_web.spinny_auth_user$data@140806201974491105] Layout: [full_name:varchar, id_23:integer] Estimates: {rows: 17988382 (438.19MB), cpu: 438.19M, memory: 0B, network: 0B} full_name := 6:full_name:varchar id_23 := 7:id:integer Fragment 17 [SOURCE] Output layout: [account_id_29] Output partitioning: HASH [account_id_29] TableScan[table = iceberg:sp_phonecall.call_logs$data@138828993269347242] Layout: [account_id_29:integer] Estimates: {rows: 128100977 (582.75MB), cpu: 582.75M, memory: 0B, network: 0B} account_id_29 := 30:account_id:integer Fragment 18 [HASH] Output layout: [id_53, source_object_id_70, source_object_type_id_71, model, display_name_100] Output partitioning: HASH [id_53] LeftJoin[criteria = (platform_id = id_101), filter = (source_object_type_id_71 IN integer '322', integer '319'), distribution = REPLICATED] │ Layout: [id_53:integer, source_object_id_70:integer, source_object_type_id_71:integer, model:varchar, display_name_100:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 9.65kB, network: 0B} │ Distribution: REPLICATED ├─ LeftJoin[criteria = (source_object_id_70 = id_94), filter = (source_object_type_id_71 IN integer '322', integer '319'), distribution = PARTITIONED] │ │ Layout: [id_53:integer, source_object_id_70:integer, source_object_type_id_71:integer, model:varchar, platform_id:integer] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 1.09kB, network: 0B} │ │ Distribution: PARTITIONED │ ├─ LeftJoin[criteria = (source_object_id_70 = id_83), distribution = PARTITIONED] │ │ │ Layout: [id_53:integer, source_object_id_70:integer, source_object_type_id_71:integer, model:varchar] │ │ │ Estimates: {rows: ? (?), cpu: ?, memory: 872.63MB, network: 0B} │ │ │ Distribution: PARTITIONED │ │ ├─ RemoteSource[sourceFragmentIds = [19]] │ │ │ Layout: [id_53:integer, source_object_id_70:integer, source_object_type_id_71:integer, model:varchar] │ │ └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=integer, name=id_83]]] │ │ │ Layout: [id_83:integer] │ │ │ Estimates: {rows: 183004002 (872.63MB), cpu: 872.63M, memory: 0B, network: 0B} │ │ └─ RemoteSource[sourceFragmentIds = [21]] │ │ Layout: [id_83:integer] │ └─ LocalExchange[partitioning = SINGLE] │ │ Layout: [id_94:integer, platform_id:integer] │ │ Estimates: {rows: 112 (1.09kB), cpu: 0, memory: 0B, network: 0B} │ └─ RemoteSource[sourceFragmentIds = [22]] │ Layout: [id_94:integer, platform_id:integer] └─ LocalExchange[partitioning = SINGLE] │ Layout: [display_name_100:varchar, id_101:integer] │ Estimates: {rows: 5 (549B), cpu: 0, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [23]] Layout: [display_name_100:varchar, id_101:integer] Fragment 19 [SOURCE] Output layout: [id_53, source_object_id_70, source_object_type_id_71, model] Output partitioning: HASH [source_object_id_70] LeftJoin[criteria = (source_object_type_id_71 = id_78), distribution = REPLICATED] │ Layout: [id_53:integer, source_object_id_70:integer, source_object_type_id_71:integer, model:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 691.35kB, network: 0B} │ Distribution: REPLICATED ├─ ScanFilterProject[table = iceberg:sp_web.buy_lead_buylead$data@1299828741364571249, filterPredicate = (CAST((created_on_46 + interval day to second '0 05:30:00.000') AS date) >= date '2018-01-30')] │ Layout: [id_53:integer, source_object_id_70:integer, source_object_type_id_71:integer] │ Estimates: {rows: 12700031 (181.61MB), cpu: 339.06M, memory: 0B, network: 0B}/{rows: 6350016 (90.81MB), cpu: 339.06M, memory: 0B, network: 0B}/{rows: 6350016 (90.81MB), cpu: 90.81M, memory: 0B, network: 0B} │ created_on_46 := 12:created_on:timestamp(6) with time zone │ source_object_id_70 := 36:source_object_id:integer │ id_53 := 19:id:integer │ source_object_type_id_71 := 37:source_object_type_id:integer └─ LocalExchange[partitioning = SINGLE] │ Layout: [id_78:integer, model:varchar] │ Estimates: {rows: 1030 (38.41kB), cpu: 0, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [20]] Layout: [id_78:integer, model:varchar] Fragment 20 [SOURCE] Output layout: [id_78, model] Output partitioning: BROADCAST [] TableScan[table = iceberg:sp_web.django_content_type$data@9009429266202918266] Layout: [id_78:integer, model:varchar] Estimates: {rows: 1030 (38.41kB), cpu: 38.41k, memory: 0B, network: 0B} id_78 := 2:id:integer model := 3:model:varchar Fragment 21 [SOURCE] Output layout: [id_83] Output partitioning: HASH [id_83] TableScan[table = iceberg:sp_web.whatsapp_message$data@7433077615325471857] Layout: [id_83:integer] Estimates: {rows: 183004002 (872.63MB), cpu: 872.63M, memory: 0B, network: 0B} id_83 := 4:id:integer Fragment 22 [SOURCE] Output layout: [id_94, platform_id] Output partitioning: HASH [id_94] TableScan[table = iceberg:sp_web.external_listing_listingplatformaccounts$data@6017462594562719178] Layout: [id_94:integer, platform_id:integer] Estimates: {rows: 112 (1.09kB), cpu: 1.09k, memory: 0B, network: 0B} platform_id := 12:platform_id:integer id_94 := 8:id:integer Fragment 23 [SOURCE] Output layout: [display_name_100, id_101] Output partitioning: BROADCAST [] TableScan[table = iceberg:sp_web.external_listing_externallistingplatform$data@3106258827814415296] Layout: [display_name_100:varchar, id_101:integer] Estimates: {rows: 5 (549B), cpu: 549, memory: 0B, network: 0B} display_name_100 := 2:display_name:varchar id_101 := 3:id:integer Fragment 24 [SOURCE] Output layout: [id_122, display_name_183] Output partitioning: HASH [id_122] LeftJoin[criteria = (platform_id_176 = id_184), distribution = REPLICATED] │ Layout: [id_122:integer, display_name_183:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 9.65kB, network: 0B} │ Distribution: REPLICATED ├─ LeftJoin[criteria = (account_id_158 = id_172), distribution = REPLICATED] │ │ Layout: [id_122:integer, platform_id_176:integer] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 19.69kB, network: 0B} │ │ Distribution: REPLICATED │ ├─ LeftJoin[criteria = (listing_id = id_161), distribution = REPLICATED] │ │ │ Layout: [id_122:integer, account_id_158:integer] │ │ │ Estimates: {rows: ? (?), cpu: ?, memory: 9.36MB, network: 0B} │ │ │ Distribution: REPLICATED │ │ ├─ LeftJoin[criteria = (source_object_id_139 = id_152), filter = (source_object_type_id_140 = integer '321'), distribution = REPLICATED] │ │ │ │ Layout: [id_122:integer, listing_id:integer] │ │ │ │ Estimates: {rows: ? (?), cpu: ?, memory: 58.23MB, network: 0B} │ │ │ │ Distribution: REPLICATED │ │ │ ├─ TableScan[table = iceberg:sp_web.buy_lead_buylead$data@1299828741364571249] │ │ │ │ Layout: [id_122:integer, source_object_id_139:integer, source_object_type_id_140:integer] │ │ │ │ Estimates: {rows: 12700031 (181.61MB), cpu: 181.61M, memory: 0B, network: 0B} │ │ │ │ id_122 := 19:id:integer │ │ │ │ source_object_type_id_140 := 37:source_object_type_id:integer │ │ │ │ source_object_id_139 := 36:source_object_id:integer │ │ │ └─ LocalExchange[partitioning = SINGLE] │ │ │ │ Layout: [id_152:integer, listing_id:integer] │ │ │ │ Estimates: {rows: 339234 (3.24MB), cpu: 0, memory: 0B, network: 0B} │ │ │ └─ RemoteSource[sourceFragmentIds = [25]] │ │ │ Layout: [id_152:integer, listing_id:integer] │ │ └─ LocalExchange[partitioning = SINGLE] │ │ │ Layout: [account_id_158:integer, id_161:integer] │ │ │ Estimates: {rows: 54520 (532.42kB), cpu: 0, memory: 0B, network: 0B} │ │ └─ RemoteSource[sourceFragmentIds = [26]] │ │ Layout: [account_id_158:integer, id_161:integer] │ └─ LocalExchange[partitioning = SINGLE] │ │ Layout: [id_172:integer, platform_id_176:integer] │ │ Estimates: {rows: 112 (1.09kB), cpu: 0, memory: 0B, network: 0B} │ └─ RemoteSource[sourceFragmentIds = [27]] │ Layout: [id_172:integer, platform_id_176:integer] └─ LocalExchange[partitioning = SINGLE] │ Layout: [display_name_183:varchar, id_184:integer] │ Estimates: {rows: 5 (549B), cpu: 0, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [28]] Layout: [display_name_183:varchar, id_184:integer] Fragment 25 [SOURCE] Output layout: [id_152, listing_id] Output partitioning: BROADCAST [] TableScan[table = iceberg:sp_web.external_listing_externalbuyrequest$data@8613310664252366845] Layout: [id_152:integer, listing_id:integer] Estimates: {rows: 339234 (3.24MB), cpu: 3.24M, memory: 0B, network: 0B} id_152 := 7:id:integer listing_id := 8:listing_id:integer Fragment 26 [SOURCE] Output layout: [account_id_158, id_161] Output partitioning: BROADCAST [] TableScan[table = iceberg:sp_web.external_listing_externallisting$data@4144789504165051730] Layout: [account_id_158:integer, id_161:integer] Estimates: {rows: 54520 (532.42kB), cpu: 532.42k, memory: 0B, network: 0B} id_161 := 4:id:integer account_id_158 := 1:account_id:integer Fragment 27 [SOURCE] Output layout: [id_172, platform_id_176] Output partitioning: BROADCAST [] TableScan[table = iceberg:sp_web.external_listing_listingplatformaccounts$data@6017462594562719178] Layout: [id_172:integer, platform_id_176:integer] Estimates: {rows: 112 (1.09kB), cpu: 1.09k, memory: 0B, network: 0B} id_172 := 8:id:integer platform_id_176 := 12:platform_id:integer Fragment 28 [SOURCE] Output layout: [display_name_183, id_184] Output partitioning: BROADCAST [] TableScan[table = iceberg:sp_web.external_listing_externallistingplatform$data@3106258827814415296] Layout: [display_name_183:varchar, id_184:integer] Estimates: {rows: 5 (549B), cpu: 549, memory: 0B, network: 0B} id_184 := 3:id:integer display_name_183 := 2:display_name:varchar Fragment 29 [SOURCE] Output layout: [id_188, url_189] Output partitioning: BROADCAST [] TableScan[table = iceberg:sp_web.webresults_webarticle$data@4621341169227520572] Layout: [id_188:integer, url_189:varchar] Estimates: {rows: 9042 (1.07MB), cpu: 1.07M, memory: 0B, network: 0B} id_188 := 3:id:integer url_189 := 5:url:varchar Fragment 30 [HASH] Output layout: [id_211, marketing_attribution_id, cta_slug] Output partitioning: HASH [id_211] Aggregate[type = FINAL, keys = [id_211, marketing_attribution_id, cta_slug]] │ Layout: [id_211:integer, marketing_attribution_id:integer, cta_slug:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=integer, name=id_211], SymbolReference[type=integer, name=marketing_attribution_id], SymbolReference[type=varchar, name=cta_slug]]] │ Layout: [id_211:integer, marketing_attribution_id:integer, cta_slug:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [31]] Layout: [id_211:integer, marketing_attribution_id:integer, cta_slug:varchar] Fragment 31 [HASH] Output layout: [id_211, marketing_attribution_id, cta_slug] Output partitioning: HASH [id_211, marketing_attribution_id, cta_slug] Aggregate[type = PARTIAL, keys = [id_211, marketing_attribution_id, cta_slug]] │ Layout: [id_211:integer, marketing_attribution_id:integer, cta_slug:varchar] └─ FilterProject[filterPredicate = (row_number_315 = bigint '1')] │ Layout: [id_211:integer, cta_slug:varchar, marketing_attribution_id:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B}/{rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ Project[] │ Layout: [id_211:integer, cta_slug:varchar, marketing_attribution_id:integer, row_number_315:bigint] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ TopNRanking[partitionBy = [buy_lead_id_236], orderBy = [log_creation_time ASC NULLS LAST], limit = 1] │ Layout: [id_211:integer, buy_lead_id_236:integer, cta_slug:varchar, log_creation_time:timestamp(6) with time zone, marketing_attribution_id:integer, row_number_315:bigint] │ row_number_315 := ROW_NUMBER └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=integer, name=buy_lead_id_236]]] │ Layout: [id_211:integer, buy_lead_id_236:integer, cta_slug:varchar, log_creation_time:timestamp(6) with time zone, marketing_attribution_id:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [32]] Layout: [id_211:integer, buy_lead_id_236:integer, cta_slug:varchar, log_creation_time:timestamp(6) with time zone, marketing_attribution_id:integer] Fragment 32 [HASH] Output layout: [id_211, buy_lead_id_236, cta_slug, log_creation_time, marketing_attribution_id] Output partitioning: HASH [buy_lead_id_236] TopNRanking[partitionBy = [buy_lead_id_236], orderBy = [log_creation_time ASC NULLS LAST], limit = 1] │ Layout: [id_211:integer, buy_lead_id_236:integer, cta_slug:varchar, log_creation_time:timestamp(6) with time zone, marketing_attribution_id:integer] │ row_number_315 := ROW_NUMBER └─ LeftJoin[criteria = (created_by_id_253 = id_298), distribution = REPLICATED] │ Layout: [id_211:integer, buy_lead_id_236:integer, cta_slug:varchar, log_creation_time:timestamp(6) with time zone, marketing_attribution_id:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: 1.51GB, network: 0B} │ Distribution: REPLICATED ├─ LeftJoin[criteria = (id_211 = context_id_251), distribution = PARTITIONED] │ │ Layout: [buy_lead_id_236:integer, cta_slug:varchar, log_creation_time:timestamp(6) with time zone, marketing_attribution_id:integer, id_211:integer, created_by_id_253:integer] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 28.39MB, network: 0B} │ │ Distribution: PARTITIONED │ ├─ RightJoin[criteria = (buy_lead_id_236 = id_211), distribution = PARTITIONED] │ │ │ Layout: [buy_lead_id_236:integer, cta_slug:varchar, log_creation_time:timestamp(6) with time zone, marketing_attribution_id:integer, id_211:integer] │ │ │ Estimates: {rows: ? (?), cpu: ?, memory: 60.56MB, network: 0B} │ │ │ Distribution: PARTITIONED │ │ │ dynamicFilterAssignments = {id_211 -> #df_16617} │ │ ├─ RemoteSource[sourceFragmentIds = [33]] │ │ │ Layout: [buy_lead_id_236:integer, cta_slug:varchar, log_creation_time:timestamp(6) with time zone, marketing_attribution_id:integer] │ │ └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=integer, name=id_211]]] │ │ │ Layout: [id_211:integer] │ │ │ Estimates: {rows: 12700031 (60.56MB), cpu: 60.56M, memory: 0B, network: 0B} │ │ └─ RemoteSource[sourceFragmentIds = [34]] │ │ Layout: [id_211:integer] │ └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=integer, name=context_id_251]]] │ │ Layout: [context_id_251:integer, created_by_id_253:integer] │ │ Estimates: {rows: 2977093 (28.39MB), cpu: 28.39M, memory: 0B, network: 0B} │ └─ RemoteSource[sourceFragmentIds = [35]] │ Layout: [context_id_251:integer, created_by_id_253:integer] └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=integer, name=id_298]]] │ Layout: [id_298:integer] │ Estimates: {rows: 17988382 (85.78MB), cpu: 85.78M, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [36]] Layout: [id_298:integer] Fragment 33 [SOURCE] Output layout: [buy_lead_id_236, cta_slug, log_creation_time, marketing_attribution_id] Output partitioning: HASH [buy_lead_id_236] ScanFilter[table = iceberg:mongo_marketing_attribution.buy_lead_cta_logs$data@6164463033804556162, dynamicFilters = {buy_lead_id_236 = #df_16617}] Layout: [buy_lead_id_236:integer, cta_slug:varchar, log_creation_time:timestamp(6) with time zone, marketing_attribution_id:integer] Estimates: {rows: 28811712 (802.69MB), cpu: 802.69M, memory: 0B, network: 0B}/{rows: 28811712 (802.69MB), cpu: 802.69M, memory: 0B, network: 0B} buy_lead_id_236 := 2:buy_lead_id:integer marketing_attribution_id := 7:marketing_attribution_id:integer cta_slug := 5:cta_slug:varchar log_creation_time := 6:log_creation_time:timestamp(6) with time zone Fragment 34 [SOURCE] Output layout: [id_211] Output partitioning: HASH [id_211] TableScan[table = iceberg:sp_web.buy_lead_buylead$data@1299828741364571249] Layout: [id_211:integer] Estimates: {rows: 12700031 (60.56MB), cpu: 60.56M, memory: 0B, network: 0B} id_211 := 19:id:integer Fragment 35 [SOURCE] Output layout: [context_id_251, created_by_id_253] Output partitioning: HASH [context_id_251] TableScan[table = iceberg:sp_web.visits_visit$data@918499440402197125] Layout: [context_id_251:integer, created_by_id_253:integer] Estimates: {rows: 2977093 (28.39MB), cpu: 28.39M, memory: 0B, network: 0B} context_id_251 := 12:context_id:integer created_by_id_253 := 14:created_by_id:integer Fragment 36 [SOURCE] Output layout: [id_298] Output partitioning: BROADCAST [] TableScan[table = iceberg:sp_web.spinny_auth_user$data@140806201974491105] Layout: [id_298:integer] Estimates: {rows: 17988382 (85.78MB), cpu: 85.78M, memory: 0B, network: 0B} id_298 := 7:id:integer Fragment 37 [HASH] Output layout: [id_334, min] Output partitioning: HASH [id_334] Project[] │ Layout: [id_334:integer, min:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ Aggregate[type = FINAL, keys = [id_334, cta_slug_363]] │ Layout: [id_334:integer, cta_slug_363:varchar, min:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} │ min := min(min_1327) └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=integer, name=id_334], SymbolReference[type=varchar, name=cta_slug_363]]] │ Layout: [id_334:integer, cta_slug_363:varchar, min_1327:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [38]] Layout: [id_334:integer, cta_slug_363:varchar, min_1327:integer] Fragment 38 [HASH] Output layout: [id_334, cta_slug_363, min_1327] Output partitioning: HASH [id_334, cta_slug_363] Aggregate[type = PARTIAL, keys = [id_334, cta_slug_363]] │ Layout: [id_334:integer, cta_slug_363:varchar, min_1327:integer] │ min_1327 := min(marketing_attribution_id_365) └─ FilterProject[filterPredicate = ((CASE WHEN ((visit_type_id_418 = integer '2') AND (category_323 = varchar 'assured') AND (is_staff_431 = integer '0') AND (cta_slug_363 = varchar 'buy_request')) THEN integer '1' ELSE integer '0' END) = integer '1')] │ Layout: [id_334:integer, cta_slug_363:varchar, marketing_attribution_id_365:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B}/{rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ LeftJoin[criteria = (created_by_id_382 = id_427), distribution = PARTITIONED] │ Layout: [category_323:varchar, id_334:integer, cta_slug_363:varchar, marketing_attribution_id_365:integer, visit_type_id_418:integer, is_staff_431:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: 171.55MB, network: 0B} │ Distribution: PARTITIONED ├─ RemoteSource[sourceFragmentIds = [39]] │ Layout: [category_323:varchar, id_334:integer, cta_slug_363:varchar, marketing_attribution_id_365:integer, created_by_id_382:integer, visit_type_id_418:integer] └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=integer, name=id_427]]] │ Layout: [id_427:integer, is_staff_431:integer] │ Estimates: {rows: 17988382 (171.55MB), cpu: 171.55M, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [43]] Layout: [id_427:integer, is_staff_431:integer] Fragment 39 [HASH] Output layout: [category_323, id_334, cta_slug_363, marketing_attribution_id_365, created_by_id_382, visit_type_id_418] Output partitioning: HASH [created_by_id_382] LeftJoin[criteria = (id_334 = context_id_380), distribution = PARTITIONED] │ Layout: [cta_slug_363:varchar, marketing_attribution_id_365:integer, category_323:varchar, id_334:integer, created_by_id_382:integer, visit_type_id_418:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: 42.59MB, network: 0B} │ Distribution: PARTITIONED ├─ RightJoin[criteria = (buy_lead_id_360 = id_334), distribution = PARTITIONED] │ │ Layout: [cta_slug_363:varchar, marketing_attribution_id_365:integer, category_323:varchar, id_334:integer] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 127.01MB, network: 0B} │ │ Distribution: PARTITIONED │ │ dynamicFilterAssignments = {id_334 -> #df_16628} │ ├─ RemoteSource[sourceFragmentIds = [40]] │ │ Layout: [buy_lead_id_360:integer, cta_slug_363:varchar, marketing_attribution_id_365:integer] │ └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=integer, name=id_334]]] │ │ Layout: [category_323:varchar, id_334:integer] │ │ Estimates: {rows: 12700031 (127.01MB), cpu: 127.01M, memory: 0B, network: 0B} │ └─ RemoteSource[sourceFragmentIds = [41]] │ Layout: [category_323:varchar, id_334:integer] └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=integer, name=context_id_380]]] │ Layout: [context_id_380:integer, created_by_id_382:integer, visit_type_id_418:integer] │ Estimates: {rows: 2977093 (42.59MB), cpu: 42.59M, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [42]] Layout: [context_id_380:integer, created_by_id_382:integer, visit_type_id_418:integer] Fragment 40 [SOURCE] Output layout: [buy_lead_id_360, cta_slug_363, marketing_attribution_id_365] Output partitioning: HASH [buy_lead_id_360] ScanFilter[table = iceberg:mongo_marketing_attribution.buy_lead_cta_logs$data@6164463033804556162, dynamicFilters = {buy_lead_id_360 = #df_16628}] Layout: [buy_lead_id_360:integer, cta_slug_363:varchar, marketing_attribution_id_365:integer] Estimates: {rows: 28811712 (445.49MB), cpu: 445.49M, memory: 0B, network: 0B}/{rows: 28811712 (445.49MB), cpu: 445.49M, memory: 0B, network: 0B} marketing_attribution_id_365 := 7:marketing_attribution_id:integer cta_slug_363 := 5:cta_slug:varchar buy_lead_id_360 := 2:buy_lead_id:integer Fragment 41 [SOURCE] Output layout: [category_323, id_334] Output partitioning: HASH [id_334] TableScan[table = iceberg:sp_web.buy_lead_buylead$data@1299828741364571249] Layout: [category_323:varchar, id_334:integer] Estimates: {rows: 12700031 (127.01MB), cpu: 127.01M, memory: 0B, network: 0B} id_334 := 19:id:integer category_323 := 8:category:varchar Fragment 42 [SOURCE] Output layout: [context_id_380, created_by_id_382, visit_type_id_418] Output partitioning: HASH [context_id_380] TableScan[table = iceberg:sp_web.visits_visit$data@918499440402197125] Layout: [context_id_380:integer, created_by_id_382:integer, visit_type_id_418:integer] Estimates: {rows: 2977093 (42.59MB), cpu: 42.59M, memory: 0B, network: 0B} visit_type_id_418 := 50:visit_type_id:integer created_by_id_382 := 14:created_by_id:integer context_id_380 := 12:context_id:integer Fragment 43 [SOURCE] Output layout: [id_427, is_staff_431] Output partitioning: HASH [id_427] TableScan[table = iceberg:sp_web.spinny_auth_user$data@140806201974491105] Layout: [id_427:integer, is_staff_431:integer] Estimates: {rows: 17988382 (171.55MB), cpu: 171.55M, memory: 0B, network: 0B} is_staff_431 := 11:is_staff:integer id_427 := 7:id:integer Fragment 44 [SOURCE] Output layout: [id_449, utm_medium, utm_source, utm_term] Output partitioning: HASH [id_449] TableScan[table = iceberg:sp_web.marketing_marketingattribution$data@5810179578041371111] Layout: [id_449:integer, utm_medium:varchar, utm_source:varchar, utm_term:varchar] Estimates: {rows: 196944231 (5.05GB), cpu: 5.05G, memory: 0B, network: 0B} utm_term := 24:utm_term:varchar utm_medium := 22:utm_medium:varchar id_449 := 11:id:integer utm_source := 23:utm_source:varchar Fragment 45 [SOURCE] Output layout: [marketing_attribution_id_458, user_activity_type] Output partitioning: HASH [marketing_attribution_id_458] TableScan[table = iceberg:sp_cw_user_data_engine.user_activity_logger_useractivitylog$data@213815406515993458] Layout: [marketing_attribution_id_458:integer, user_activity_type:varchar] Estimates: {rows: 12125080 (117.48MB), cpu: 117.48M, memory: 0B, network: 0B} marketing_attribution_id_458 := 6:marketing_attribution_id:integer user_activity_type := 7:user_activity_type:varchar Fragment 46 [SOURCE] Output layout: [id_464] Output partitioning: BROADCAST [] TableScan[table = iceberg:sp_web.address_hub$data@7203458224615821150] Layout: [id_464:integer] Estimates: {rows: 141 (705B), cpu: 705, memory: 0B, network: 0B} id_464 := 24:id:integer Fragment 47 [SOURCE] Output layout: [display_name_471, id_472] Output partitioning: BROADCAST [] TableScan[table = iceberg:sp_web.address_city$data@3145091731273200997] Layout: [display_name_471:varchar, id_472:integer] Estimates: {rows: 454 (15.32kB), cpu: 15.32k, memory: 0B, network: 0B} id_472 := 5:id:integer display_name_471 := 3:display_name:varchar Fragment 48 [SOURCE] Output layout: [sell_lead_id_483, visit_id] Output partitioning: BROADCAST [] TableScan[table = iceberg:sp_web.buy_lead_testdrive$data@329118448009893483] Layout: [sell_lead_id_483:integer, visit_id:integer] Estimates: {rows: 3116766 (29.72MB), cpu: 29.72M, memory: 0B, network: 0B} visit_id := 20:visit_id:integer sell_lead_id_483 := 17:sell_lead_id:integer Fragment 49 [SOURCE] Output layout: [id_495, profile_id, tag_status] Output partitioning: HASH [id_495] TableScan[table = iceberg:sp_web.listing_lead$data@654511650163888914] Layout: [id_495:integer, profile_id:integer, tag_status:varchar] Estimates: {rows: 14393538 (210.65MB), cpu: 210.65M, memory: 0B, network: 0B} id_495 := 26:id:integer profile_id := 55:profile_id:integer tag_status := 70:tag_status:varchar Fragment 50 [SOURCE] Output layout: [id_513, registration_no] Output partitioning: HASH [id_513] TableScan[table = iceberg:sp_web.listing_leadprofile$data@3752956674780667051] Layout: [id_513:integer, registration_no:varchar] Estimates: {rows: 26793658 (513.68MB), cpu: 513.68M, memory: 0B, network: 0B} id_513 := 21:id:integer registration_no := 77:registration_no:varchar Fragment 51 [SOURCE] Output layout: [id_524] Output partitioning: BROADCAST [] ScanFilterProject[table = iceberg:sp_web.status_status$data@4176504356023197209, filterPredicate = (NOT system.builtin.$like(description_523, LikePattern '[%Cancel%]'))] Layout: [id_524:integer] Estimates: {rows: 604 (2.95kB), cpu: 29.74k, memory: 0B, network: 0B}/{rows: ? (?), cpu: 29.74k, memory: 0B, network: 0B}/{rows: ? (?), cpu: ?, memory: 0B, network: 0B} description_523 := 3:description:varchar id_524 := 5:id:integer Fragment 52 [HASH] Output layout: [expr_1316, expr_1318, id_610] Output partitioning: HASH [expr_1318] Project[] │ Layout: [expr_1316:varchar(14), expr_1318:varchar, id_610:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ expr_1318 := CAST(id_610 AS varchar) └─ Project[] │ Layout: [id_610:integer, expr_1316:varchar(14)] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ Aggregate[keys = [id_610, expr_1316, expr_1292, expr_1297]] │ Layout: [id_610:integer, expr_1316:varchar(14), expr_1292:varchar, expr_1297:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} └─ Project[] │ Layout: [expr_1316:varchar(14), expr_1292:varchar, expr_1297:varchar, id_610:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ expr_1316 := (CASE WHEN (expr_1315 = varchar '591918414') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar '{offer_ref_id}') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar '3dot14') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'acemediaplus_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'adapptmobi') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'adcanopus') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'adcanopus_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'adcountryindia') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'adcountymedia_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'adpiece_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'adsvmedia_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'affinityveve') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'affleagency') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'amazus_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'appfloodaff_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'appitate_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'applabs_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'applabsmedia') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'appmontize') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'Appmontize1') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'appnext_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'atmoicads_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'backgardon_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'betop_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'blueocean_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'cheeringads_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'cooins_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'CRM') THEN varchar(14) 'App_CRM' WHEN (expr_1315 = varchar 'dech_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'dehheit_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'digitalverse_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'erinlabs') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'Facebook Ads') THEN varchar(14) 'App_Facebook' WHEN (expr_1315 = varchar 'gads_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'glance_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'googleadwords_int') THEN varchar(14) 'App_Google' WHEN (expr_1315 = varchar 'gourdmobiads_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'hasoffers_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'Hotstar') THEN varchar(14) 'App_Hotstar' WHEN (expr_1315 = varchar 'Hotstar') THEN varchar(14) 'App_Hotstar' WHEN (expr_1315 = varchar 'icolorfast_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'icubeswire') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'inmobi_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'inmobiagency') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'intellect_ads') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'intellectads') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'jumboads') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'kickcash_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'linmobi_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'livetopmedia_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'madcube_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'maopumedia_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'marlinads_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'mediaversedigis') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'mediaxpediatech') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'mobavenue') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'mobfountain2') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'mobpine_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'mobuppagency') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'mobupps_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'mobuppsagency') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'mobwide_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'mocaglobal') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'multiads_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'oneenginemedia') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'Organic') THEN varchar(14) 'App_Organic' WHEN (expr_1315 = varchar 'orilmobi_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'plusgamesgo_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'poche_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'pokktmkt') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'pokktperformance_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'prodigital') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'profuseservices_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'QR_code') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'QR_code') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'restricted') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'restricted') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'royomobi_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'seikoads_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'sharechat_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'siftco_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'simplyverses_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'Spinny') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'Spinny_Affle_PanIndia') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'Spinny_Android') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'Spotify') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'starrytech_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'surfertech_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'taboola_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'Tarsan') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'tempoads_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'test') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'test_fb_ak') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'tjzymob_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'TVF_Youtube') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'upsflyer_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'vcommission') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'verseiume_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'vestaapps_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'vidmobads_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'vserv') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'WhatsApp') THEN varchar(14) 'App_Whatsapp' WHEN (expr_1315 = varchar 'xyadsagency') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'axismobi') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'adzealous') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'econnectmobi') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'applabsmedia') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'magixengage') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'Auto-Car-Video') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'fillymedia') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'quickadsmedia') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'inmobidsp_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'blendaidigital') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'Apple Search Ads') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'ballyhoomedia') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'nativemonetize') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'Appnext') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'Email') THEN varchar(14) 'App_CRM' WHEN (expr_1315 = varchar 'Social_instagram') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'mobavenue_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'Survey') THEN varchar(14) 'App_CRM' WHEN (expr_1315 = varchar 'lucrative') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'aimarkit') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'flickstree') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'GlobalWideMedia') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'geoadmedia_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'globalwide_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'mobisaturntechn') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'mrndigital') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'unilead_network') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'optimidea') THEN varchar(14) 'App_Affiliates' WHEN (expr_1315 = varchar 'zorkanetwork') THEN varchar(14) 'App_Affiliates' ELSE varchar(14) 'App_organic' END) └─ Project[] │ Layout: [id_610:integer, expr_1315:varchar, expr_1297:varchar, expr_1292:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ Aggregate[type = FINAL, keys = [id_610, expr_1313, expr_1314, expr_1295, expr_1294, display_name_1300, expr_1293, expr_1315, expr_1296, expr_1297, expr_1292]] │ Layout: [id_610:integer, expr_1313:varchar(6), expr_1314:varchar(2), expr_1295:varchar, expr_1294:varchar, display_name_1300:varchar, expr_1293:varchar, expr_1315:varchar, expr_1296:date, expr_1297:varchar, expr_1292:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=integer, name=id_610], SymbolReference[type=varchar, name=expr_1297], SymbolReference[type=varchar, name=expr_1292]]] │ Layout: [id_610:integer, expr_1313:varchar(6), expr_1314:varchar(2), expr_1295:varchar, expr_1294:varchar, display_name_1300:varchar, expr_1293:varchar, expr_1315:varchar, expr_1296:date, expr_1297:varchar, expr_1292:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ Aggregate[type = PARTIAL, keys = [id_610, expr_1313, expr_1314, expr_1295, expr_1294, display_name_1300, expr_1293, expr_1315, expr_1296, expr_1297, expr_1292]] │ Layout: [id_610:integer, expr_1313:varchar(6), expr_1314:varchar(2), expr_1295:varchar, expr_1294:varchar, display_name_1300:varchar, expr_1293:varchar, expr_1315:varchar, expr_1296:date, expr_1297:varchar, expr_1292:varchar] └─ Project[] │ Layout: [expr_1315:varchar, expr_1292:varchar, expr_1293:varchar, expr_1294:varchar, expr_1295:varchar, expr_1296:date, expr_1297:varchar, display_name_1300:varchar, id_610:integer, expr_1313:varchar(6), expr_1314:varchar(2)] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ expr_1315 := (CASE WHEN (expr_1294 = varchar '') THEN expr_1293 ELSE expr_1294 END) │ expr_1313 := (CASE WHEN system.builtin.$like(platform_source_619, LikePattern '[%app_%]') THEN varchar(6) 'App' WHEN system.builtin.$like(platform_source_619, LikePattern '[%web%]') THEN varchar(6) 'Web' WHEN system.builtin.$like(platform_source_619, LikePattern '[%mweb_%]') THEN varchar(6) 'Web' ELSE varchar(6) 'Others' END) │ expr_1314 := (CASE WHEN system.builtin.$like(expr_1292, LikePattern '[%RM%]') THEN varchar(2) 'RM' WHEN system.builtin.$like(expr_1292, LikePattern '[%PR%]') THEN varchar(2) 'PR' END) └─ LeftJoin[criteria = (city_id_600 = id_1302), distribution = REPLICATED] │ Layout: [id_610:integer, platform_source_619:varchar, expr_1292:varchar, expr_1293:varchar, expr_1294:varchar, expr_1295:varchar, expr_1296:date, expr_1297:varchar, display_name_1300:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 275.71kB, network: 0B} │ Distribution: REPLICATED │ maySkipOutputDuplicates = true ├─ LeftJoin[criteria = (id_610 = expr_1290), distribution = PARTITIONED] │ │ Layout: [city_id_600:integer, platform_source_619:varchar, id_610:integer, expr_1292:varchar, expr_1293:varchar, expr_1294:varchar, expr_1295:varchar, expr_1296:date, expr_1297:varchar] │ │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} │ │ Distribution: PARTITIONED │ │ maySkipOutputDuplicates = true │ ├─ InnerJoin[criteria = (id_610 = context_id_551), distribution = PARTITIONED] │ │ │ Layout: [city_id_600:integer, id_610:integer, platform_source_619:varchar] │ │ │ Estimates: {rows: ? (?), cpu: ?, memory: 7.10MB, network: 0B} │ │ │ Distribution: PARTITIONED │ │ │ maySkipOutputDuplicates = true │ │ │ dynamicFilterAssignments = {context_id_551 -> #df_16662} │ │ ├─ RemoteSource[sourceFragmentIds = [53]] │ │ │ Layout: [city_id_600:integer, id_610:integer, platform_source_619:varchar] │ │ └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=integer, name=context_id_551]]] │ │ │ Layout: [context_id_551:integer] │ │ │ Estimates: {rows: 1488525 (7.10MB), cpu: 7.10M, memory: 0B, network: 0B} │ │ └─ RemoteSource[sourceFragmentIds = [54]] │ │ Layout: [context_id_551:integer] │ └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=integer, name=expr_1290]]] │ │ Layout: [expr_1290:integer, expr_1292:varchar, expr_1293:varchar, expr_1294:varchar, expr_1295:varchar, expr_1296:date, expr_1297:varchar] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ └─ RemoteSource[sourceFragmentIds = [55]] │ Layout: [expr_1290:integer, expr_1292:varchar, expr_1293:varchar, expr_1294:varchar, expr_1295:varchar, expr_1296:date, expr_1297:varchar] └─ LocalExchange[partitioning = SINGLE] │ Layout: [display_name_1300:varchar, id_1302:integer] │ Estimates: {rows: 454 (15.32kB), cpu: 0, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [74]] Layout: [display_name_1300:varchar, id_1302:integer] Fragment 53 [SOURCE] Output layout: [city_id_600, id_610, platform_source_619] Output partitioning: HASH [id_610] ScanFilterProject[table = iceberg:sp_web.buy_lead_buylead$data@1299828741364571249, filterPredicate = ((category_599 = varchar 'assured') AND system.builtin.$like(platform_source_619, LikePattern '[%app%]')), dynamicFilters = {id_610 = #df_16662}] Layout: [city_id_600:integer, id_610:integer, platform_source_619:varchar] Estimates: {rows: 12700031 (191.60MB), cpu: 258.05M, memory: 0B, network: 0B}/{rows: 5715014 (86.22MB), cpu: 258.05M, memory: 0B, network: 0B}/{rows: 5715014 (86.22MB), cpu: 86.22M, memory: 0B, network: 0B} platform_source_619 := 28:platform_source:varchar category_599 := 8:category:varchar id_610 := 19:id:integer city_id_600 := 9:city_id:integer Fragment 54 [SOURCE] Output layout: [context_id_551] Output partitioning: HASH [context_id_551] ScanFilterProject[table = iceberg:sp_web.visits_visit$data@918499440402197125, filterPredicate = (CAST((created_on_554 + interval day to second '0 05:30:00.000') AS date) >= date '2024-03-12')] Layout: [context_id_551:integer] Estimates: {rows: 2977093 (14.20MB), cpu: 51.10M, memory: 0B, network: 0B}/{rows: 1488525 (7.10MB), cpu: 51.10M, memory: 0B, network: 0B}/{rows: 1488525 (7.10MB), cpu: 7.10M, memory: 0B, network: 0B} context_id_551 := 12:context_id:integer created_on_554 := 15:created_on:timestamp(6) with time zone Fragment 55 [HASH] Output layout: [expr_1290, expr_1292, expr_1293, expr_1294, expr_1295, expr_1296, expr_1297] Output partitioning: HASH [expr_1290] Project[] │ Layout: [expr_1290:integer, expr_1292:varchar, expr_1293:varchar, expr_1294:varchar, expr_1295:varchar, expr_1296:date, expr_1297:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ expr_1290 := COALESCE(id_968, id_705) │ expr_1292 := COALESCE(campaign_1160, campaign_778) │ expr_1293 := COALESCE(media_source_1229, media_source_847) │ expr_1294 := COALESCE(partner_1237, partner_855) │ expr_1295 := COALESCE(platform_1239, platform_857) │ expr_1296 := COALESCE(expr_1269, expr_887) │ expr_1297 := COALESCE(adset_1141, adset_759) └─ FullJoin[criteria = (id_705 = id_968), distribution = PARTITIONED] │ Layout: [id_705:integer, campaign_778:varchar, media_source_847:varchar, partner_855:varchar, platform_857:varchar, expr_887:date, adset_759:varchar, id_968:integer, campaign_1160:varchar, media_source_1229:varchar, partner_1237:varchar, platform_1239:varchar, expr_1269:date, adset_1141:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} │ Distribution: PARTITIONED │ maySkipOutputDuplicates = true ├─ FilterProject[filterPredicate = (row_number_896 = bigint '1')] │ │ Layout: [id_705:integer, campaign_778:varchar, media_source_847:varchar, partner_855:varchar, platform_857:varchar, expr_887:date, adset_759:varchar] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B}/{rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ └─ Project[] │ │ Layout: [id_705:integer, campaign_778:varchar, media_source_847:varchar, partner_855:varchar, platform_857:varchar, expr_887:date, adset_759:varchar, row_number_896:bigint] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ └─ TopNRanking[partitionBy = [id_705], orderBy = [event_time_822 DESC NULLS LAST], limit = 1] │ │ Layout: [id_705:integer, campaign_778:varchar, event_time_822:varchar, media_source_847:varchar, partner_855:varchar, platform_857:varchar, expr_887:date, adset_759:varchar, row_number_896:bigint] │ │ row_number_896 := ROW_NUMBER │ └─ Project[] │ │ Layout: [id_705:integer, campaign_778:varchar, event_time_822:varchar, media_source_847:varchar, partner_855:varchar, platform_857:varchar, expr_887:date, adset_759:varchar] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ └─ TopNRanking[partitionBy = [id_705], orderBy = [event_time_822 DESC NULLS LAST], limit = 1] │ │ Layout: [adset_759:varchar, campaign_778:varchar, event_time_822:varchar, platform_857:varchar, partner_855:varchar, media_source_847:varchar, id_705:integer, expr_887:date, row_number_895:bigint] │ │ row_number_895 := ROW_NUMBER │ └─ FilterProject[filterPredicate = (dense_rank_894 = bigint '1')] │ │ Layout: [adset_759:varchar, campaign_778:varchar, event_time_822:varchar, platform_857:varchar, partner_855:varchar, media_source_847:varchar, id_705:integer, expr_887:date] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B}/{rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ └─ Project[] │ │ Layout: [adset_759:varchar, campaign_778:varchar, event_time_822:varchar, platform_857:varchar, partner_855:varchar, media_source_847:varchar, id_705:integer, expr_887:date, dense_rank_894:bigint] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ └─ Window[partitionBy = [], orderBy = [expr_893 DESC NULLS LAST]] │ │ Layout: [adset_759:varchar, campaign_778:varchar, event_time_822:varchar, platform_857:varchar, expr_893:integer, partner_855:varchar, media_source_847:varchar, id_705:integer, expr_887:date, dense_rank_894:bigint] │ │ dense_rank_894 := dense_rank() RANGE UNBOUNDED_PRECEDING CURRENT_ROW │ └─ FilterProject[filterPredicate = (dense_rank = bigint '1')] │ │ Layout: [adset_759:varchar, campaign_778:varchar, event_time_822:varchar, platform_857:varchar, expr_893:integer, partner_855:varchar, media_source_847:varchar, id_705:integer, expr_887:date] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B}/{rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ │ expr_893 := ((max + max_891) + max_892) │ └─ Window[partitionBy = [id_705], orderBy = [max DESC NULLS LAST]] │ │ Layout: [id_705:integer, campaign_778:varchar, event_time_822:varchar, media_source_847:varchar, partner_855:varchar, platform_857:varchar, expr_887:date, adset_759:varchar, max:integer, max_891:integer, max_892:integer, dense_rank:bigint] │ │ dense_rank := dense_rank() RANGE UNBOUNDED_PRECEDING CURRENT_ROW │ └─ Project[] │ │ Layout: [id_705:integer, campaign_778:varchar, event_time_822:varchar, media_source_847:varchar, partner_855:varchar, platform_857:varchar, expr_887:date, adset_759:varchar, max:integer, max_891:integer, max_892:integer] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ └─ Aggregate[keys = [id_705, expr_753, event_name_817, campaign_778, event_time_822, expr_883, media_source_847, partner_855, platform_857, expr_887, adset_759]] │ │ Layout: [id_705:integer, expr_753:date, event_name_817:varchar, campaign_778:varchar, event_time_822:varchar, expr_883:timestamp(3), media_source_847:varchar, partner_855:varchar, platform_857:varchar, expr_887:date, adset_759:varchar, max:integer, max_891:integer, max_892:integer] │ │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} │ │ max := max(expr_884) │ │ max_891 := max(expr_885) │ │ max_892 := max(expr_886) │ └─ Project[] │ │ Layout: [id_705:integer, expr_753:date, event_name_817:varchar, campaign_778:varchar, media_source_847:varchar, platform_857:varchar, partner_855:varchar, adset_759:varchar, expr_883:timestamp(3), event_time_822:varchar, expr_884:integer, expr_885:integer, expr_886:integer, expr_887:date] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ └─ Aggregate[keys = [id_705, expr_753, event_name_817, campaign_778, media_source_847, platform_857, partner_855, is_primary_attribution_839, is_retargeting_841, adset_759, expr_883, event_time_822, row_number_882, expr_884, expr_885, expr_886, expr_887]] │ │ Layout: [id_705:integer, expr_753:date, event_name_817:varchar, campaign_778:varchar, media_source_847:varchar, platform_857:varchar, partner_855:varchar, is_primary_attribution_839:varchar, is_retargeting_841:varchar, adset_759:varchar, expr_883:timestamp(3), event_time_822:varchar, row_number_882:bigint, expr_884:integer, expr_885:integer, expr_886:integer, expr_887:date] │ │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} │ └─ Project[] │ │ Layout: [id_705:integer, adset_759:varchar, campaign_778:varchar, is_primary_attribution_839:varchar, platform_857:varchar, row_number_882:bigint, event_name_817:varchar, media_source_847:varchar, is_retargeting_841:varchar, event_time_822:varchar, expr_753:date, expr_885:integer, expr_884:integer, expr_883:timestamp(3), partner_855:varchar, expr_887:date, expr_886:integer] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ │ expr_885 := (CASE WHEN (is_primary_attribution_839 = varchar 'true') THEN integer '1' ELSE integer '0' END) │ │ expr_884 := (CASE WHEN (event_name_817 = varchar 'af_demand_q3') THEN integer '3' WHEN (event_name_817 = varchar 'af_demand_q2') THEN integer '2' WHEN (event_name_817 = varchar 'af_demand_q1') THEN integer '1' ELSE integer '0' END) │ │ expr_883 := (CASE WHEN (system.builtin.length(system.builtin.trim(event_time_822)) = bigint '0') THEN null::timestamp(3) WHEN system.builtin.$like(event_time_822, LikePattern '[%T%]') THEN system.builtin.date_parse(event_time_822, varchar(18) '%Y-%m-%dT%H:%i:%sZ') ELSE system.builtin.date_parse(event_time_822, varchar(17) '%Y-%m-%d %H:%i:%s') END) │ │ expr_887 := CAST(((CASE WHEN (system.builtin.length(system.builtin.trim(install_time_836)) = bigint '0') THEN null::timestamp(3) WHEN system.builtin.$like(install_time_836, LikePattern '[%T%]') THEN system.builtin.date_parse(install_time_836, varchar(18) '%Y-%m-%dT%H:%i:%sZ') ELSE system.builtin.date_parse(install_time_836, varchar(17) '%Y-%m-%d %H:%i:%s') END) + interval day to second '0 05:30:00.000') AS date) │ │ expr_886 := (CASE WHEN (is_retargeting_841 = varchar 'true') THEN integer '1' ELSE integer '0' END) │ └─ Window[partitionBy = [id_705], orderBy = [event_time_822 DESC NULLS LAST]] │ │ Layout: [id_705:integer, expr_753:date, adset_759:varchar, campaign_778:varchar, event_name_817:varchar, event_time_822:varchar, install_time_836:varchar, is_primary_attribution_839:varchar, is_retargeting_841:varchar, media_source_847:varchar, partner_855:varchar, platform_857:varchar, row_number_882:bigint] │ │ row_number_882 := row_number() RANGE UNBOUNDED_PRECEDING CURRENT_ROW │ └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=integer, name=id_705]]] │ │ Layout: [id_705:integer, expr_753:date, adset_759:varchar, campaign_778:varchar, event_name_817:varchar, event_time_822:varchar, install_time_836:varchar, is_primary_attribution_839:varchar, is_retargeting_841:varchar, media_source_847:varchar, partner_855:varchar, platform_857:varchar] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ └─ RemoteSource[sourceFragmentIds = [56]] │ Layout: [id_705:integer, expr_753:date, adset_759:varchar, campaign_778:varchar, event_name_817:varchar, event_time_822:varchar, install_time_836:varchar, is_primary_attribution_839:varchar, is_retargeting_841:varchar, media_source_847:varchar, partner_855:varchar, platform_857:varchar] └─ FilterProject[filterPredicate = (row_number_1288 = bigint '1')] │ Layout: [id_968:integer, campaign_1160:varchar, media_source_1229:varchar, partner_1237:varchar, platform_1239:varchar, expr_1269:date, adset_1141:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B}/{rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ Project[] │ Layout: [id_968:integer, campaign_1160:varchar, media_source_1229:varchar, partner_1237:varchar, platform_1239:varchar, expr_1269:date, adset_1141:varchar, row_number_1288:bigint] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ TopNRanking[partitionBy = [id_968], orderBy = [event_time_1204 DESC NULLS LAST], limit = 1] │ Layout: [id_968:integer, campaign_1160:varchar, event_time_1204:varchar, media_source_1229:varchar, partner_1237:varchar, platform_1239:varchar, expr_1269:date, adset_1141:varchar, row_number_1288:bigint] │ row_number_1288 := ROW_NUMBER └─ Project[] │ Layout: [id_968:integer, campaign_1160:varchar, event_time_1204:varchar, media_source_1229:varchar, partner_1237:varchar, platform_1239:varchar, expr_1269:date, adset_1141:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ TopNRanking[partitionBy = [id_968], orderBy = [event_time_1204 DESC NULLS LAST], limit = 1] │ Layout: [platform_1239:varchar, adset_1141:varchar, id_968:integer, media_source_1229:varchar, event_time_1204:varchar, campaign_1160:varchar, partner_1237:varchar, expr_1269:date, row_number_1287:bigint] │ row_number_1287 := ROW_NUMBER └─ FilterProject[filterPredicate = (dense_rank_1286 = bigint '1')] │ Layout: [platform_1239:varchar, adset_1141:varchar, id_968:integer, media_source_1229:varchar, event_time_1204:varchar, campaign_1160:varchar, partner_1237:varchar, expr_1269:date] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B}/{rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ Project[] │ Layout: [platform_1239:varchar, adset_1141:varchar, id_968:integer, media_source_1229:varchar, event_time_1204:varchar, campaign_1160:varchar, partner_1237:varchar, expr_1269:date, dense_rank_1286:bigint] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ Window[partitionBy = [], orderBy = [expr_1285 DESC NULLS LAST]] │ Layout: [platform_1239:varchar, adset_1141:varchar, id_968:integer, media_source_1229:varchar, event_time_1204:varchar, campaign_1160:varchar, expr_1285:integer, partner_1237:varchar, expr_1269:date, dense_rank_1286:bigint] │ dense_rank_1286 := dense_rank() RANGE UNBOUNDED_PRECEDING CURRENT_ROW └─ FilterProject[filterPredicate = (dense_rank_1284 = bigint '1')] │ Layout: [platform_1239:varchar, adset_1141:varchar, id_968:integer, media_source_1229:varchar, event_time_1204:varchar, campaign_1160:varchar, expr_1285:integer, partner_1237:varchar, expr_1269:date] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B}/{rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ expr_1285 := ((max_1281 + max_1282) + max_1283) └─ Window[partitionBy = [id_968], orderBy = [max_1281 DESC NULLS LAST]] │ Layout: [id_968:integer, campaign_1160:varchar, event_time_1204:varchar, media_source_1229:varchar, partner_1237:varchar, platform_1239:varchar, expr_1269:date, adset_1141:varchar, max_1281:integer, max_1282:integer, max_1283:integer, dense_rank_1284:bigint] │ dense_rank_1284 := dense_rank() RANGE UNBOUNDED_PRECEDING CURRENT_ROW └─ Project[] │ Layout: [id_968:integer, campaign_1160:varchar, event_time_1204:varchar, media_source_1229:varchar, partner_1237:varchar, platform_1239:varchar, expr_1269:date, adset_1141:varchar, max_1281:integer, max_1282:integer, max_1283:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ Aggregate[keys = [id_968, expr_1135, event_name_1199, campaign_1160, event_time_1204, expr_1265, media_source_1229, partner_1237, platform_1239, expr_1269, adset_1141]] │ Layout: [id_968:integer, expr_1135:date, event_name_1199:varchar, campaign_1160:varchar, event_time_1204:varchar, expr_1265:timestamp(3), media_source_1229:varchar, partner_1237:varchar, platform_1239:varchar, expr_1269:date, adset_1141:varchar, max_1281:integer, max_1282:integer, max_1283:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} │ max_1281 := max(expr_1266) │ max_1282 := max(expr_1267) │ max_1283 := max(expr_1268) └─ Project[] │ Layout: [id_968:integer, expr_1135:date, event_name_1199:varchar, campaign_1160:varchar, media_source_1229:varchar, platform_1239:varchar, partner_1237:varchar, adset_1141:varchar, expr_1265:timestamp(3), event_time_1204:varchar, expr_1266:integer, expr_1267:integer, expr_1268:integer, expr_1269:date] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ Aggregate[keys = [id_968, expr_1135, event_name_1199, campaign_1160, media_source_1229, platform_1239, partner_1237, is_primary_attribution_1221, is_retargeting_1223, adset_1141, expr_1265, event_time_1204, row_number_1264, expr_1266, expr_1267, expr_1268, expr_1269]] │ Layout: [id_968:integer, expr_1135:date, event_name_1199:varchar, campaign_1160:varchar, media_source_1229:varchar, platform_1239:varchar, partner_1237:varchar, is_primary_attribution_1221:varchar, is_retargeting_1223:varchar, adset_1141:varchar, expr_1265:timestamp(3), event_time_1204:varchar, row_number_1264:bigint, expr_1266:integer, expr_1267:integer, expr_1268:integer, expr_1269:date] │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} └─ FilterProject[filterPredicate = (event_name_1199 = varchar 'af_demand_q3')] │ Layout: [platform_1239:varchar, is_primary_attribution_1221:varchar, media_source_1229:varchar, campaign_1160:varchar, expr_1265:timestamp(3), expr_1266:integer, expr_1135:date, expr_1267:integer, id_968:integer, expr_1268:integer, expr_1269:date, event_name_1199:varchar, is_retargeting_1223:varchar, adset_1141:varchar, event_time_1204:varchar, partner_1237:varchar, row_number_1264:bigint] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B}/{rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ expr_1265 := (CASE WHEN (system.builtin.length(system.builtin.trim(event_time_1204)) = bigint '0') THEN null::timestamp(3) WHEN system.builtin.$like(event_time_1204, LikePattern '[%T%]') THEN system.builtin.date_parse(event_time_1204, varchar(18) '%Y-%m-%dT%H:%i:%sZ') ELSE system.builtin.date_parse(event_time_1204, varchar(17) '%Y-%m-%d %H:%i:%s') END) │ expr_1266 := (CASE WHEN (event_name_1199 = varchar 'af_demand_q3') THEN integer '3' WHEN (event_name_1199 = varchar 'af_demand_q2') THEN integer '2' WHEN (event_name_1199 = varchar 'af_demand_q1') THEN integer '1' ELSE integer '0' END) │ expr_1267 := (CASE WHEN (is_primary_attribution_1221 = varchar 'true') THEN integer '1' ELSE integer '0' END) │ expr_1268 := (CASE WHEN (is_retargeting_1223 = varchar 'true') THEN integer '1' ELSE integer '0' END) │ expr_1269 := CAST(((CASE WHEN (system.builtin.length(system.builtin.trim(install_time_1218)) = bigint '0') THEN null::timestamp(3) WHEN system.builtin.$like(install_time_1218, LikePattern '[%T%]') THEN system.builtin.date_parse(install_time_1218, varchar(18) '%Y-%m-%dT%H:%i:%sZ') ELSE system.builtin.date_parse(install_time_1218, varchar(17) '%Y-%m-%d %H:%i:%s') END) + interval day to second '0 05:30:00.000') AS date) └─ Window[partitionBy = [id_968], orderBy = [event_time_1204 DESC NULLS LAST]] │ Layout: [id_968:integer, expr_1135:date, adset_1141:varchar, campaign_1160:varchar, event_name_1199:varchar, event_time_1204:varchar, install_time_1218:varchar, is_primary_attribution_1221:varchar, is_retargeting_1223:varchar, media_source_1229:varchar, partner_1237:varchar, platform_1239:varchar, row_number_1264:bigint] │ row_number_1264 := row_number() RANGE UNBOUNDED_PRECEDING CURRENT_ROW └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=integer, name=id_968]]] │ Layout: [id_968:integer, expr_1135:date, adset_1141:varchar, campaign_1160:varchar, event_name_1199:varchar, event_time_1204:varchar, install_time_1218:varchar, is_primary_attribution_1221:varchar, is_retargeting_1223:varchar, media_source_1229:varchar, partner_1237:varchar, platform_1239:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [65]] Layout: [id_968:integer, expr_1135:date, adset_1141:varchar, campaign_1160:varchar, event_name_1199:varchar, event_time_1204:varchar, install_time_1218:varchar, is_primary_attribution_1221:varchar, is_retargeting_1223:varchar, media_source_1229:varchar, partner_1237:varchar, platform_1239:varchar] Fragment 56 [HASH] Output layout: [id_705, expr_753, adset_759, campaign_778, event_name_817, event_time_822, install_time_836, is_primary_attribution_839, is_retargeting_841, media_source_847, partner_855, platform_857] Output partitioning: HASH [id_705] InnerJoin[criteria = (device_id = customer_user_id_809), filter = (expr_1323 <= CAST((created_on_649 + interval day to second '0 05:30:00.000') AS date)), distribution = PARTITIONED] │ Layout: [id_705:integer, expr_753:date, adset_759:varchar, campaign_778:varchar, event_name_817:varchar, event_time_822:varchar, install_time_836:varchar, is_primary_attribution_839:varchar, is_retargeting_841:varchar, media_source_847:varchar, partner_855:varchar, platform_857:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 32.91GB, network: 0B} │ Distribution: PARTITIONED ├─ RemoteSource[sourceFragmentIds = [57]] │ Layout: [id_705:integer, device_id:varchar, created_on_649:timestamp(6) with time zone, expr_753:date] └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=varchar, name=customer_user_id_809]]] │ Layout: [adset_759:varchar, campaign_778:varchar, event_time_822:varchar, is_primary_attribution_839:varchar, install_time_836:varchar, platform_857:varchar, event_name_817:varchar, customer_user_id_809:varchar, partner_855:varchar, media_source_847:varchar, expr_1323:date, is_retargeting_841:varchar] │ Estimates: {rows: 68803562 (32.91GB), cpu: 32.91G, memory: 0B, network: 0B} └─ Project[] │ Layout: [adset_759:varchar, campaign_778:varchar, event_time_822:varchar, is_primary_attribution_839:varchar, install_time_836:varchar, platform_857:varchar, event_name_817:varchar, customer_user_id_809:varchar, partner_855:varchar, media_source_847:varchar, expr_1323:date, is_retargeting_841:varchar] │ Estimates: {rows: 68803562 (32.91GB), cpu: 32.91G, memory: 0B, network: 0B} │ expr_1323 := CAST(((CASE WHEN (system.builtin.length(system.builtin.trim(event_time_822)) = bigint '0') THEN null::timestamp(3) WHEN system.builtin.$like(event_time_822, LikePattern '[%T%]') THEN system.builtin.date_parse(event_time_822, varchar(18) '%Y-%m-%dT%H:%i:%sZ') ELSE system.builtin.date_parse(event_time_822, varchar(17) '%Y-%m-%d %H:%i:%s') END) + interval day to second '0 05:30:00.000') AS date) └─ RemoteSource[sourceFragmentIds = [64]] Layout: [adset_759:varchar, campaign_778:varchar, customer_user_id_809:varchar, event_name_817:varchar, event_time_822:varchar, install_time_836:varchar, is_primary_attribution_839:varchar, is_retargeting_841:varchar, media_source_847:varchar, partner_855:varchar, platform_857:varchar] Fragment 57 [HASH] Output layout: [id_705, device_id, created_on_649, expr_753] Output partitioning: HASH [device_id] Project[] │ Layout: [id_705:integer, device_id:varchar, created_on_649:timestamp(6) with time zone, expr_753:date] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ Aggregate[keys = [id_705, device_id, row_number_752, created_on_649, expr_753]] │ Layout: [id_705:integer, device_id:varchar, row_number_752:bigint, created_on_649:timestamp(6) with time zone, expr_753:date] │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} └─ FilterProject[filterPredicate = (row_number_752 = bigint '1')] │ Layout: [id_705:integer, device_id:varchar, expr_753:date, row_number_752:bigint, created_on_649:timestamp(6) with time zone] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B}/{rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ expr_753 := CAST((created_on_698 + interval day to second '0 05:30:00.000') AS date) └─ Project[] │ Layout: [created_on_649:timestamp(6) with time zone, created_on_698:timestamp(6) with time zone, id_705:integer, device_id:varchar, row_number_752:bigint] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ TopNRanking[partitionBy = [id_705], orderBy = [event_time DESC NULLS LAST], limit = 1] │ Layout: [created_on_649:timestamp(6) with time zone, created_on_698:timestamp(6) with time zone, id_705:integer, device_id:varchar, event_time:varchar, row_number_752:bigint] │ row_number_752 := ROW_NUMBER └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=integer, name=id_705]]] │ Layout: [created_on_649:timestamp(6) with time zone, created_on_698:timestamp(6) with time zone, id_705:integer, device_id:varchar, event_time:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [58]] Layout: [created_on_649:timestamp(6) with time zone, created_on_698:timestamp(6) with time zone, id_705:integer, device_id:varchar, event_time:varchar] Fragment 58 [HASH] Output layout: [created_on_649, created_on_698, id_705, device_id, event_time] Output partitioning: HASH [id_705] TopNRanking[partitionBy = [id_705], orderBy = [event_time DESC NULLS LAST], limit = 1] │ Layout: [created_on_649:timestamp(6) with time zone, id_705:integer, created_on_698:timestamp(6) with time zone, device_id:varchar, event_time:varchar] │ row_number_752 := ROW_NUMBER └─ InnerJoin[criteria = (device_id = customer_user_id), filter = (expr_1324 <= CAST((created_on_649 + interval day to second '0 05:30:00.000') AS date)), distribution = PARTITIONED] │ Layout: [created_on_649:timestamp(6) with time zone, id_705:integer, created_on_698:timestamp(6) with time zone, device_id:varchar, event_time:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} │ Distribution: PARTITIONED │ dynamicFilterAssignments = {customer_user_id -> #df_16670} ├─ RemoteSource[sourceFragmentIds = [59]] │ Layout: [created_on_649:timestamp(6) with time zone, id_705:integer, created_on_698:timestamp(6) with time zone, device_id:varchar] └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=varchar, name=customer_user_id]]] │ Layout: [customer_user_id:varchar, event_time:varchar, expr_1324:date] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ Project[] │ Layout: [customer_user_id:varchar, event_time:varchar, expr_1324:date] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ expr_1324 := CAST(((CASE WHEN (system.builtin.length(system.builtin.trim(event_time)) = bigint '0') THEN null::timestamp(3) WHEN system.builtin.$like(event_time, LikePattern '[%T%]') THEN system.builtin.date_parse(event_time, varchar(18) '%Y-%m-%dT%H:%i:%sZ') ELSE system.builtin.date_parse(event_time, varchar(17) '%Y-%m-%d %H:%i:%s') END) + interval day to second '0 05:30:00.000') AS date) └─ RemoteSource[sourceFragmentIds = [63]] Layout: [customer_user_id:varchar, event_time:varchar] Fragment 59 [HASH] Output layout: [created_on_649, id_705, created_on_698, device_id] Output partitioning: HASH [device_id] InnerJoin[criteria = (account_id_687 = account_id_730), distribution = PARTITIONED] │ Layout: [created_on_698:timestamp(6) with time zone, id_705:integer, created_on_649:timestamp(6) with time zone, device_id:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 988.54MB, network: 0B} │ Distribution: PARTITIONED │ dynamicFilterAssignments = {account_id_730 -> #df_16672} ├─ RemoteSource[sourceFragmentIds = [60]] │ Layout: [account_id_687:integer, created_on_698:timestamp(6) with time zone, id_705:integer, created_on_649:timestamp(6) with time zone] └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=integer, name=account_id_730]]] │ Layout: [account_id_730:integer, device_id:varchar] │ Estimates: {rows: 7530135 (988.54MB), cpu: 988.54M, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [62]] Layout: [account_id_730:integer, device_id:varchar] Fragment 60 [SOURCE] Output layout: [account_id_687, created_on_698, id_705, created_on_649] Output partitioning: HASH [account_id_687] InnerJoin[criteria = (id_705 = context_id_646), distribution = REPLICATED] │ Layout: [account_id_687:integer, created_on_698:timestamp(6) with time zone, id_705:integer, created_on_649:timestamp(6) with time zone] │ Estimates: {rows: ? (?), cpu: ?, memory: 459.94MB, network: 0B} │ Distribution: REPLICATED │ dynamicFilterAssignments = {context_id_646 -> #df_16673} ├─ ScanFilterProject[table = iceberg:sp_web.buy_lead_buylead$data@1299828741364571249, filterPredicate = system.builtin.$like(platform_source_714, LikePattern '[%app%]'), dynamicFilters = {account_id_687 = #df_16672, id_705 = #df_16673}] │ Layout: [account_id_687:integer, created_on_698:timestamp(6) with time zone, id_705:integer] │ Estimates: {rows: 12700031 (278.56MB), cpu: 349.15M, memory: 0B, network: 0B}/{rows: 11430028 (250.70MB), cpu: 349.15M, memory: 0B, network: 0B}/{rows: 11430028 (250.70MB), cpu: 250.70M, memory: 0B, network: 0B} │ created_on_698 := 12:created_on:timestamp(6) with time zone │ platform_source_714 := 28:platform_source:varchar │ id_705 := 19:id:integer │ account_id_687 := 1:account_id:integer └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=integer, name=context_id_646]]] │ Layout: [context_id_646:integer, created_on_649:timestamp(6) with time zone] │ Estimates: {rows: 1488525 (25.55MB), cpu: 25.55M, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [61]] Layout: [context_id_646:integer, created_on_649:timestamp(6) with time zone] Fragment 61 [SOURCE] Output layout: [context_id_646, created_on_649] Output partitioning: BROADCAST [] ScanFilter[table = iceberg:sp_web.visits_visit$data@918499440402197125, filterPredicate = (CAST((created_on_649 + interval day to second '0 05:30:00.000') AS date) >= date '2024-03-12')] Layout: [context_id_646:integer, created_on_649:timestamp(6) with time zone] Estimates: {rows: 2977093 (51.10MB), cpu: 51.10M, memory: 0B, network: 0B}/{rows: 1488525 (25.55MB), cpu: 51.10M, memory: 0B, network: 0B} context_id_646 := 12:context_id:integer created_on_649 := 15:created_on:timestamp(6) with time zone Fragment 62 [SOURCE] Output layout: [account_id_730, device_id] Output partitioning: HASH [account_id_730] ScanFilter[table = iceberg:sp_cw_user_data_engine.user_meta_info_accountmetadata$data@550938720318740374, dynamicFilters = {device_id = #df_16670}] Layout: [account_id_730:integer, device_id:varchar] Estimates: {rows: 7530135 (988.54MB), cpu: 988.54M, memory: 0B, network: 0B}/{rows: 7530135 (988.54MB), cpu: 988.54M, memory: 0B, network: 0B} device_id := 3:device_id:varchar account_id_730 := 1:account_id:integer Fragment 63 [SOURCE] Output layout: [customer_user_id, event_time] Output partitioning: HASH [customer_user_id] ScanFilterProject[table = iceberg:mongo_marketing_attribution.appsflyer_event_data$data@2902615493133821655 constraint on [sp_created_at], filterPredicate = ((event_name IN varchar 'af_demand_q1', varchar 'af_demand_q2', varchar 'af_demand_q3', varchar 'af_supply_l1', varchar 'af_supply_l2', varchar 'af_supply_l3', varchar 'install', varchar 're-attribution', varchar 're-engagement', varchar 'reinstall') AND system.builtin.$like(app_name, LikePattern '[%Spinny%]'))] Layout: [customer_user_id:varchar, event_time:varchar] Estimates: {rows: 68803562 (7.05GB), cpu: 10.89G, memory: 0B, network: 0B}/{rows: ? (?), cpu: 10.89G, memory: 0B, network: 0B}/{rows: ? (?), cpu: ?, memory: 0B, network: 0B} app_name := 12:app_name:varchar event_name := 64:event_name:varchar customer_user_id := 56:customer_user_id:varchar event_time := 69:event_time:varchar 114:sp_created_at:timestamp(6) with time zone :: [[2024-03-12 00:00:00.000000 UTC, )] Fragment 64 [SOURCE] Output layout: [adset_759, campaign_778, customer_user_id_809, event_name_817, event_time_822, install_time_836, is_primary_attribution_839, is_retargeting_841, media_source_847, partner_855, platform_857] Output partitioning: HASH [customer_user_id_809] TableScan[table = iceberg:mongo_marketing_attribution.appsflyer_event_data$data@2902615493133821655 constraint on [sp_created_at]] Layout: [adset_759:varchar, campaign_778:varchar, customer_user_id_809:varchar, event_name_817:varchar, event_time_822:varchar, install_time_836:varchar, is_primary_attribution_839:varchar, is_retargeting_841:varchar, media_source_847:varchar, partner_855:varchar, platform_857:varchar] Estimates: {rows: 68803562 (32.58GB), cpu: 32.58G, memory: 0B, network: 0B} adset_759 := 6:adset:varchar campaign_778 := 25:campaign:varchar event_time_822 := 69:event_time:varchar is_primary_attribution_839 := 86:is_primary_attribution:varchar install_time_836 := 83:install_time:varchar platform_857 := 104:platform:varchar event_name_817 := 64:event_name:varchar customer_user_id_809 := 56:customer_user_id:varchar partner_855 := 102:partner:varchar media_source_847 := 94:media_source:varchar is_retargeting_841 := 88:is_retargeting:varchar 114:sp_created_at:timestamp(6) with time zone :: [[2024-03-12 00:00:00.000000 UTC, )] Fragment 65 [HASH] Output layout: [id_968, expr_1135, adset_1141, campaign_1160, event_name_1199, event_time_1204, install_time_1218, is_primary_attribution_1221, is_retargeting_1223, media_source_1229, partner_1237, platform_1239] Output partitioning: HASH [id_968] InnerJoin[criteria = (device_id_995 = customer_user_id_1191), filter = (expr_1325 <= CAST((created_on_912 + interval day to second '0 05:30:00.000') AS date)), distribution = PARTITIONED] │ Layout: [id_968:integer, expr_1135:date, adset_1141:varchar, campaign_1160:varchar, event_name_1199:varchar, event_time_1204:varchar, install_time_1218:varchar, is_primary_attribution_1221:varchar, is_retargeting_1223:varchar, media_source_1229:varchar, partner_1237:varchar, platform_1239:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 32.91GB, network: 0B} │ Distribution: PARTITIONED ├─ RemoteSource[sourceFragmentIds = [66]] │ Layout: [id_968:integer, device_id_995:varchar, created_on_912:timestamp(6) with time zone, expr_1135:date] └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=varchar, name=customer_user_id_1191]]] │ Layout: [platform_1239:varchar, adset_1141:varchar, customer_user_id_1191:varchar, is_primary_attribution_1221:varchar, media_source_1229:varchar, event_time_1204:varchar, campaign_1160:varchar, install_time_1218:varchar, partner_1237:varchar, event_name_1199:varchar, is_retargeting_1223:varchar, expr_1325:date] │ Estimates: {rows: 68803562 (32.91GB), cpu: 32.91G, memory: 0B, network: 0B} └─ Project[] │ Layout: [platform_1239:varchar, adset_1141:varchar, customer_user_id_1191:varchar, is_primary_attribution_1221:varchar, media_source_1229:varchar, event_time_1204:varchar, campaign_1160:varchar, install_time_1218:varchar, partner_1237:varchar, event_name_1199:varchar, is_retargeting_1223:varchar, expr_1325:date] │ Estimates: {rows: 68803562 (32.91GB), cpu: 32.91G, memory: 0B, network: 0B} │ expr_1325 := CAST(((CASE WHEN (system.builtin.length(system.builtin.trim(event_time_1204)) = bigint '0') THEN null::timestamp(3) WHEN system.builtin.$like(event_time_1204, LikePattern '[%T%]') THEN system.builtin.date_parse(event_time_1204, varchar(18) '%Y-%m-%dT%H:%i:%sZ') ELSE system.builtin.date_parse(event_time_1204, varchar(17) '%Y-%m-%d %H:%i:%s') END) + interval day to second '0 05:30:00.000') AS date) └─ RemoteSource[sourceFragmentIds = [73]] Layout: [adset_1141:varchar, campaign_1160:varchar, customer_user_id_1191:varchar, event_name_1199:varchar, event_time_1204:varchar, install_time_1218:varchar, is_primary_attribution_1221:varchar, is_retargeting_1223:varchar, media_source_1229:varchar, partner_1237:varchar, platform_1239:varchar] Fragment 66 [HASH] Output layout: [id_968, device_id_995, created_on_912, expr_1135] Output partitioning: HASH [device_id_995] Project[] │ Layout: [id_968:integer, device_id_995:varchar, created_on_912:timestamp(6) with time zone, expr_1135:date] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ Aggregate[keys = [id_968, device_id_995, row_number_1134, created_on_912, expr_1135]] │ Layout: [id_968:integer, device_id_995:varchar, row_number_1134:bigint, created_on_912:timestamp(6) with time zone, expr_1135:date] │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} └─ FilterProject[filterPredicate = (row_number_1134 = bigint '1')] │ Layout: [device_id_995:varchar, expr_1135:date, created_on_912:timestamp(6) with time zone, id_968:integer, row_number_1134:bigint] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B}/{rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ expr_1135 := CAST((created_on_961 + interval day to second '0 05:30:00.000') AS date) └─ Project[] │ Layout: [created_on_912:timestamp(6) with time zone, created_on_961:timestamp(6) with time zone, id_968:integer, device_id_995:varchar, row_number_1134:bigint] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ TopNRanking[partitionBy = [id_968], orderBy = [event_time_1074 DESC NULLS LAST], limit = 1] │ Layout: [created_on_912:timestamp(6) with time zone, created_on_961:timestamp(6) with time zone, id_968:integer, device_id_995:varchar, event_time_1074:varchar, row_number_1134:bigint] │ row_number_1134 := ROW_NUMBER └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=integer, name=id_968]]] │ Layout: [created_on_912:timestamp(6) with time zone, created_on_961:timestamp(6) with time zone, id_968:integer, device_id_995:varchar, event_time_1074:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [67]] Layout: [created_on_912:timestamp(6) with time zone, created_on_961:timestamp(6) with time zone, id_968:integer, device_id_995:varchar, event_time_1074:varchar] Fragment 67 [HASH] Output layout: [created_on_912, created_on_961, id_968, device_id_995, event_time_1074] Output partitioning: HASH [id_968] TopNRanking[partitionBy = [id_968], orderBy = [event_time_1074 DESC NULLS LAST], limit = 1] │ Layout: [created_on_912:timestamp(6) with time zone, id_968:integer, created_on_961:timestamp(6) with time zone, device_id_995:varchar, event_time_1074:varchar] │ row_number_1134 := ROW_NUMBER └─ InnerJoin[criteria = (device_id_995 = customer_user_id_1061), filter = (expr_1326 <= CAST((created_on_912 + interval day to second '0 05:30:00.000') AS date)), distribution = PARTITIONED] │ Layout: [created_on_912:timestamp(6) with time zone, id_968:integer, created_on_961:timestamp(6) with time zone, device_id_995:varchar, event_time_1074:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} │ Distribution: PARTITIONED │ dynamicFilterAssignments = {customer_user_id_1061 -> #df_16696} ├─ RemoteSource[sourceFragmentIds = [68]] │ Layout: [created_on_912:timestamp(6) with time zone, id_968:integer, created_on_961:timestamp(6) with time zone, device_id_995:varchar] └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=varchar, name=customer_user_id_1061]]] │ Layout: [expr_1326:date, customer_user_id_1061:varchar, event_time_1074:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ Project[] │ Layout: [expr_1326:date, customer_user_id_1061:varchar, event_time_1074:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ expr_1326 := CAST(((CASE WHEN (system.builtin.length(system.builtin.trim(event_time_1074)) = bigint '0') THEN null::timestamp(3) WHEN system.builtin.$like(event_time_1074, LikePattern '[%T%]') THEN system.builtin.date_parse(event_time_1074, varchar(18) '%Y-%m-%dT%H:%i:%sZ') ELSE system.builtin.date_parse(event_time_1074, varchar(17) '%Y-%m-%d %H:%i:%s') END) + interval day to second '0 05:30:00.000') AS date) └─ RemoteSource[sourceFragmentIds = [72]] Layout: [customer_user_id_1061:varchar, event_time_1074:varchar] Fragment 68 [HASH] Output layout: [created_on_912, id_968, created_on_961, device_id_995] Output partitioning: HASH [device_id_995] InnerJoin[criteria = (account_id_950 = account_id_993), distribution = PARTITIONED] │ Layout: [created_on_961:timestamp(6) with time zone, id_968:integer, created_on_912:timestamp(6) with time zone, device_id_995:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 988.54MB, network: 0B} │ Distribution: PARTITIONED │ dynamicFilterAssignments = {account_id_993 -> #df_16698} ├─ RemoteSource[sourceFragmentIds = [69]] │ Layout: [account_id_950:integer, created_on_961:timestamp(6) with time zone, id_968:integer, created_on_912:timestamp(6) with time zone] └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=integer, name=account_id_993]]] │ Layout: [account_id_993:integer, device_id_995:varchar] │ Estimates: {rows: 7530135 (988.54MB), cpu: 988.54M, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [71]] Layout: [account_id_993:integer, device_id_995:varchar] Fragment 69 [SOURCE] Output layout: [account_id_950, created_on_961, id_968, created_on_912] Output partitioning: HASH [account_id_950] InnerJoin[criteria = (id_968 = context_id_909), distribution = REPLICATED] │ Layout: [account_id_950:integer, created_on_961:timestamp(6) with time zone, id_968:integer, created_on_912:timestamp(6) with time zone] │ Estimates: {rows: ? (?), cpu: ?, memory: 459.94MB, network: 0B} │ Distribution: REPLICATED │ dynamicFilterAssignments = {context_id_909 -> #df_16699} ├─ ScanFilterProject[table = iceberg:sp_web.buy_lead_buylead$data@1299828741364571249, filterPredicate = system.builtin.$like(platform_source_977, LikePattern '[%app_%]'), dynamicFilters = {account_id_950 = #df_16698, id_968 = #df_16699}] │ Layout: [account_id_950:integer, created_on_961:timestamp(6) with time zone, id_968:integer] │ Estimates: {rows: 12700031 (278.56MB), cpu: 349.15M, memory: 0B, network: 0B}/{rows: 11430028 (250.70MB), cpu: 349.15M, memory: 0B, network: 0B}/{rows: 11430028 (250.70MB), cpu: 250.70M, memory: 0B, network: 0B} │ platform_source_977 := 28:platform_source:varchar │ created_on_961 := 12:created_on:timestamp(6) with time zone │ id_968 := 19:id:integer │ account_id_950 := 1:account_id:integer └─ LocalExchange[partitioning = HASH, arguments = [SymbolReference[type=integer, name=context_id_909]]] │ Layout: [context_id_909:integer, created_on_912:timestamp(6) with time zone] │ Estimates: {rows: 1488525 (25.55MB), cpu: 25.55M, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [70]] Layout: [context_id_909:integer, created_on_912:timestamp(6) with time zone] Fragment 70 [SOURCE] Output layout: [context_id_909, created_on_912] Output partitioning: BROADCAST [] ScanFilter[table = iceberg:sp_web.visits_visit$data@918499440402197125, filterPredicate = (CAST((created_on_912 + interval day to second '0 05:30:00.000') AS date) >= date '2024-03-12')] Layout: [context_id_909:integer, created_on_912:timestamp(6) with time zone] Estimates: {rows: 2977093 (51.10MB), cpu: 51.10M, memory: 0B, network: 0B}/{rows: 1488525 (25.55MB), cpu: 51.10M, memory: 0B, network: 0B} context_id_909 := 12:context_id:integer created_on_912 := 15:created_on:timestamp(6) with time zone Fragment 71 [SOURCE] Output layout: [account_id_993, device_id_995] Output partitioning: HASH [account_id_993] ScanFilter[table = iceberg:sp_cw_user_data_engine.user_meta_info_accountmetadata$data@550938720318740374, dynamicFilters = {device_id_995 = #df_16696}] Layout: [account_id_993:integer, device_id_995:varchar] Estimates: {rows: 7530135 (988.54MB), cpu: 988.54M, memory: 0B, network: 0B}/{rows: 7530135 (988.54MB), cpu: 988.54M, memory: 0B, network: 0B} device_id_995 := 3:device_id:varchar account_id_993 := 1:account_id:integer Fragment 72 [SOURCE] Output layout: [customer_user_id_1061, event_time_1074] Output partitioning: HASH [customer_user_id_1061] ScanFilterProject[table = iceberg:mongo_marketing_attribution.appsflyer_event_data$data@2902615493133821655 constraint on [sp_created_at], filterPredicate = ((event_name_1069 IN varchar 'af_demand_q1', varchar 'af_demand_q2', varchar 'af_demand_q3', varchar 'af_supply_l1', varchar 'af_supply_l2', varchar 'af_supply_l3', varchar 'install', varchar 're-attribution', varchar 're-engagement', varchar 'reinstall') AND system.builtin.$like(app_name_1017, LikePattern '[%Spinny%]'))] Layout: [customer_user_id_1061:varchar, event_time_1074:varchar] Estimates: {rows: 68803562 (7.05GB), cpu: 10.89G, memory: 0B, network: 0B}/{rows: ? (?), cpu: 10.89G, memory: 0B, network: 0B}/{rows: ? (?), cpu: ?, memory: 0B, network: 0B} event_name_1069 := 64:event_name:varchar app_name_1017 := 12:app_name:varchar customer_user_id_1061 := 56:customer_user_id:varchar event_time_1074 := 69:event_time:varchar 114:sp_created_at:timestamp(6) with time zone :: [[2024-03-12 00:00:00.000000 UTC, )] Fragment 73 [SOURCE] Output layout: [adset_1141, campaign_1160, customer_user_id_1191, event_name_1199, event_time_1204, install_time_1218, is_primary_attribution_1221, is_retargeting_1223, media_source_1229, partner_1237, platform_1239] Output partitioning: HASH [customer_user_id_1191] TableScan[table = iceberg:mongo_marketing_attribution.appsflyer_event_data$data@2902615493133821655 constraint on [sp_created_at]] Layout: [adset_1141:varchar, campaign_1160:varchar, customer_user_id_1191:varchar, event_name_1199:varchar, event_time_1204:varchar, install_time_1218:varchar, is_primary_attribution_1221:varchar, is_retargeting_1223:varchar, media_source_1229:varchar, partner_1237:varchar, platform_1239:varchar] Estimates: {rows: 68803562 (32.58GB), cpu: 32.58G, memory: 0B, network: 0B} platform_1239 := 104:platform:varchar adset_1141 := 6:adset:varchar customer_user_id_1191 := 56:customer_user_id:varchar is_primary_attribution_1221 := 86:is_primary_attribution:varchar media_source_1229 := 94:media_source:varchar event_time_1204 := 69:event_time:varchar campaign_1160 := 25:campaign:varchar install_time_1218 := 83:install_time:varchar partner_1237 := 102:partner:varchar event_name_1199 := 64:event_name:varchar is_retargeting_1223 := 88:is_retargeting:varchar 114:sp_created_at:timestamp(6) with time zone :: [[2024-03-12 00:00:00.000000 UTC, )] Fragment 74 [SOURCE] Output layout: [display_name_1300, id_1302] Output partitioning: BROADCAST [] TableScan[table = iceberg:sp_web.address_city$data@3145091731273200997] Layout: [display_name_1300:varchar, id_1302:integer] Estimates: {rows: 454 (15.32kB), cpu: 15.32k, memory: 0B, network: 0B} display_name_1300 := 3:display_name:varchar id_1302 := 5:id:integer

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query plan in version 447:

Trino version: 447 Fragment 0 [SINGLE] Output layout: [expr_538, expr_532, expr_1306, expr_1307, expr_533, expr_1308, expr_1309, expr_540, expr_539, expr_536, id_611, id_4] Output partitioning: SINGLE [] Output[columnNames = [city, Start_date, utmmedium, utmsource, platform, LOB, Source2, Source_Category, Assigned_lead_CT, Walkin_type, app_id, context_id]] │ Layout: [expr_538:varchar, expr_532:date, expr_1306:varchar(16), expr_1307:varchar(10), expr_533:varchar(6), expr_1308:varchar(9), expr_1309:varchar, expr_540:varchar(7), expr_539:varchar(12), expr_536:varchar(3), id_611:integer, id_4:integer] │ Estimates: {rows: 100 (49.80kB), cpu: 0, memory: 0B, network: 0B} │ city := expr_538 │ Start_date := expr_532 │ utmmedium := expr_1306 │ utmsource := expr_1307 │ platform := expr_533 │ LOB := expr_1308 │ Source2 := expr_1309 │ Source_Category := expr_540 │ Assigned_lead_CT := expr_539 │ Walkin_type := expr_536 │ app_id := id_611 │ context_id := id_4 └─ TopN[count = 100, orderBy = [expr_532 DESC NULLS LAST]] │ Layout: [expr_538:varchar, expr_532:date, expr_1306:varchar(16), expr_1307:varchar(10), expr_533:varchar(6), expr_1308:varchar(9), expr_1309:varchar, expr_540:varchar(7), expr_539:varchar(12), expr_536:varchar(3), id_611:integer, id_4:integer] │ Estimates: {rows: 100 (49.80kB), cpu: ?, memory: ?, network: ?} └─ LocalExchange[partitioning = SINGLE] │ Layout: [expr_538:varchar, expr_532:date, expr_1306:varchar(16), expr_1307:varchar(10), expr_533:varchar(6), expr_1308:varchar(9), expr_1309:varchar, expr_540:varchar(7), expr_539:varchar(12), expr_536:varchar(3), id_611:integer, id_4:integer] │ Estimates: {rows: ? (?), cpu: 0, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [1]] Layout: [expr_538:varchar, expr_532:date, expr_1306:varchar(16), expr_1307:varchar(10), expr_533:varchar(6), expr_1308:varchar(9), expr_1309:varchar, expr_540:varchar(7), expr_539:varchar(12), expr_536:varchar(3), id_611:integer, id_4:integer] Fragment 1 [HASH] Output layout: [expr_538, expr_532, expr_1306, expr_1307, expr_533, expr_1308, expr_1309, expr_540, expr_539, expr_536, id_611, id_4] Output partitioning: SINGLE [] TopNPartial[count = 100, orderBy = [expr_532 DESC NULLS LAST]] │ Layout: [expr_538:varchar, expr_532:date, expr_1306:varchar(16), expr_1307:varchar(10), expr_533:varchar(6), expr_1308:varchar(9), expr_1309:varchar, expr_540:varchar(7), expr_539:varchar(12), expr_536:varchar(3), id_611:integer, id_4:integer] └─ LocalExchange[partitioning = SINGLE] │ Layout: [expr_538:varchar, expr_532:date, expr_1306:varchar(16), expr_1307:varchar(10), expr_533:varchar(6), expr_1308:varchar(9), expr_1309:varchar, expr_540:varchar(7), expr_539:varchar(12), expr_536:varchar(3), id_611:integer, id_4:integer] │ Estimates: {rows: ? (?), cpu: 0, memory: 0B, network: 0B} └─ TopNPartial[count = 100, orderBy = [expr_532 DESC NULLS LAST]] │ Layout: [expr_538:varchar, expr_532:date, expr_1306:varchar(16), expr_1307:varchar(10), expr_533:varchar(6), expr_1308:varchar(9), expr_1309:varchar, expr_540:varchar(7), expr_539:varchar(12), expr_536:varchar(3), id_611:integer, id_4:integer] └─ LocalExchange[partitioning = ROUND_ROBIN] │ Layout: [expr_538:varchar, expr_532:date, expr_1306:varchar(16), expr_1307:varchar(10), expr_533:varchar(6), expr_1308:varchar(9), expr_1309:varchar, expr_540:varchar(7), expr_539:varchar(12), expr_536:varchar(3), id_611:integer, id_4:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ TopNPartial[count = 100, orderBy = [expr_532 DESC NULLS LAST]] │ Layout: [expr_538:varchar, expr_532:date, expr_1306:varchar(16), expr_1307:varchar(10), expr_533:varchar(6), expr_1308:varchar(9), expr_1309:varchar, expr_540:varchar(7), expr_539:varchar(12), expr_536:varchar(3), id_611:integer, id_4:integer] └─ Aggregate[type = FINAL, keys = [expr_538, expr_532, expr_1306, expr_1307, expr_533, expr_1308, expr_1309, expr_540, expr_539, expr_536, id_611, id_4]] │ Layout: [expr_538:varchar, expr_532:date, expr_1306:varchar(16), expr_1307:varchar(10), expr_533:varchar(6), expr_1308:varchar(9), expr_1309:varchar, expr_540:varchar(7), expr_539:varchar(12), expr_536:varchar(3), id_611:integer, id_4:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} └─ LocalExchange[partitioning = HASH, arguments = [expr_538::varchar, expr_532::date, expr_1306::varchar(16), expr_1307::varchar(10), expr_533::varchar(6), expr_1308::varchar(9), expr_1309::varchar, expr_540::varchar(7), expr_539::varchar(12), expr_536::varchar(3), id_611::integer, id_4::integer]] │ Layout: [expr_538:varchar, expr_532:date, expr_1306:varchar(16), expr_1307:varchar(10), expr_533:varchar(6), expr_1308:varchar(9), expr_1309:varchar, expr_540:varchar(7), expr_539:varchar(12), expr_536:varchar(3), id_611:integer, id_4:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [2]] Layout: [expr_538:varchar, expr_532:date, expr_1306:varchar(16), expr_1307:varchar(10), expr_533:varchar(6), expr_1308:varchar(9), expr_1309:varchar, expr_540:varchar(7), expr_539:varchar(12), expr_536:varchar(3), id_611:integer, id_4:integer] Fragment 2 [HASH] Output layout: [expr_538, expr_532, expr_1306, expr_1307, expr_533, expr_1308, expr_1309, expr_540, expr_539, expr_536, id_611, id_4] Output partitioning: HASH [expr_538, expr_532, expr_1306, expr_1307, expr_533, expr_1308, expr_1309, expr_540, expr_539, expr_536, id_611, id_4] Aggregate[type = PARTIAL, keys = [expr_538, expr_532, expr_1306, expr_1307, expr_533, expr_1308, expr_1309, expr_540, expr_539, expr_536, id_611, id_4]] │ Layout: [expr_538:varchar, expr_532:date, expr_1306:varchar(16), expr_1307:varchar(10), expr_533:varchar(6), expr_1308:varchar(9), expr_1309:varchar, expr_540:varchar(7), expr_539:varchar(12), expr_536:varchar(3), id_611:integer, id_4:integer] └─ Project[] │ Layout: [id_4:integer, expr_532:date, expr_533:varchar(6), expr_536:varchar(3), expr_538:varchar, expr_539:varchar(12), expr_540:varchar(7), id_611:integer, expr_1306:varchar(16), expr_1307:varchar(10), expr_1308:varchar(9), expr_1309:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ expr_1306 := (CASE WHEN (utm_medium = varchar 'truebil') THEN varchar(16) 'truebil' WHEN (utm_source = varchar 'truebil') THEN varchar(16) 'truebil' WHEN (utm_term = varchar 'TruebilBudgetRedirect') THEN varchar(16) 'truebil' WHEN (CAST(id_611 AS varchar) = CAST(id_4 AS varchar)) THEN CAST(expr_1303 AS varchar(16)) WHEN ((utm_source = varchar 'direct') AND (utm_medium IS NULL)) THEN varchar(16) 'Direct' WHEN ((utm_source = varchar 'direct') AND (utm_medium = varchar '')) THEN varchar(16) 'Direct' WHEN ((utm_source = varchar 'organic') AND (utm_medium = varchar '')) THEN varchar(16) 'Organic' WHEN ((utm_source = varchar 'organic') AND (utm_medium IS NULL)) THEN varchar(16) 'Organic' WHEN ((utm_source = varchar '') AND (utm_medium = varchar '')) THEN varchar(16) 'Organic' WHEN ((utm_source IS NULL) AND (utm_medium IS NULL)) THEN varchar(16) 'Organic' WHEN (utm_medium = varchar 'fbad') THEN varchar(16) 'Facebook' WHEN (utm_medium = varchar 'FBboost') THEN varchar(16) 'Facebook' WHEN (utm_medium = varchar 'cpm') THEN varchar(16) 'Facebook' WHEN (utm_medium = varchar 'affiliate_demand') THEN varchar(16) 'Affiliate' WHEN (utm_source IN (varchar 'Taboola', varchar 'adgebra', varchar 'outbrain')) THEN varchar(16) 'Native' WHEN (utm_medium = varchar 'partnerships') THEN varchar(16) 'Partnerships' WHEN ((utm_medium IN (varchar 'gads_t_search', varchar 'gads_c_search', varchar 'gads_m_search', varchar 'bingads_c_search', varchar 'bingads_m_search', varchar 'bingads_t_search')) AND $like(utm_source, LikePattern '[%Brand%]')) THEN varchar(16) 'SEM Brand' WHEN ((utm_medium IN (varchar 'gads_t_search', varchar 'gads_c_search', varchar 'gads_m_search', varchar 'bingads_c_search', varchar 'bingads_m_search', varchar 'bingads_t_search')) AND (NOT $like(utm_source, LikePattern '[%Brand%]'))) THEN varchar(16) 'SEM Non Brand' WHEN ($like(utm_medium, LikePattern '[%whatsapp%]') OR $like(utm_medium, LikePattern '[%sms%]') OR $like(utm_medium, LikePattern '[%push%]') OR $like(utm_medium, LikePattern '[%whatsapp=utm_campaign=supply-lead-created_abn1nkm%]') OR $like(utm_medium, LikePattern '[%webpush%]') OR $like(utm_medium, LikePattern '[%WhatsappGetDetailsTD%]') OR $like(utm_medium, LikePattern '[%whatsapp_promotional%]') OR $like(utm_medium, LikePattern '[%email%]') OR $like(utm_source, LikePattern '[%whatsapp_share%]')) THEN varchar(16) 'CRM' WHEN (utm_medium = varchar 'gads_t_video') THEN varchar(16) 'Youtube' WHEN (utm_medium = varchar 'gads_c_video') THEN varchar(16) 'Youtube' WHEN (utm_medium = varchar 'gads_m_video') THEN varchar(16) 'Youtube' WHEN (utm_medium = varchar 'gads_m_discovery') THEN varchar(16) 'Discovery' WHEN (utm_medium = varchar 'gads_t_discovery') THEN varchar(16) 'Discovery' WHEN (utm_medium = varchar 'gads_c_discovery') THEN varchar(16) 'Discovery' WHEN (utm_medium = varchar 'gads_t_display') THEN varchar(16) 'Display' WHEN (utm_medium = varchar 'gads_c_display') THEN varchar(16) 'Display' WHEN (utm_medium = varchar 'gads_m_display') THEN varchar(16) 'Display' WHEN (utm_medium = varchar 'affiliate') THEN varchar(16) 'Supply_Affiliate' ELSE varchar(16) 'Others' END) │ expr_1307 := (CASE WHEN ((utm_medium IN (varchar 'fbad', varchar 'FBboost', varchar 'gads_m_display', varchar 'gads_c_display', varchar 'gads_t_display', varchar 'gads_m_video', varchar 'gads_c_video', varchar 'gads_t_video', varchar 'gads_c_discovery', varchar 'gads_t_discovery', varchar 'gads_m_discovery')) AND $like(utm_source, LikePattern '[%RM%]')) THEN varchar(10) 'RM' WHEN ((utm_medium IN (varchar 'fbad', varchar 'FBboost', varchar 'gads_m_display', varchar 'gads_c_display', varchar 'gads_t_display', varchar 'gads_m_video', varchar 'gads_c_video', varchar 'gads_t_video', varchar 'gads_c_discovery', varchar 'gads_t_discovery', varchar 'gads_m_discovery')) AND (NOT $like(utm_source, LikePattern '[%RM%]'))) THEN varchar(10) 'PR' WHEN $like(utm_source, LikePattern '[%Remarketing%]') THEN varchar(10) 'RM' WHEN (utm_medium = varchar 'email') THEN varchar(10) 'email' WHEN (utm_medium = varchar 'sms') THEN varchar(10) 'sms' WHEN (utm_medium = varchar 'webpush') THEN varchar(10) 'Webpush' WHEN (utm_medium = varchar 'push') THEN varchar(10) 'Push' WHEN (utm_medium = varchar 'whatsapp') THEN varchar(10) 'Whatsapp' WHEN (utm_medium = varchar 'affiliate_demand') THEN varchar(10) 'Website' WHEN (CAST(expr_534 AS integer) IN (integer '473', integer '1027', integer '1028', integer '1029', integer '1050', integer '1051', integer '1052', integer '1054', integer '1055', integer '1056', integer '1057')) THEN varchar(10) 'MissedCall' WHEN (utm_source = varchar 'truebil') THEN varchar(10) 'truebil' ELSE varchar(10) 'Others' END) │ expr_1308 := (CASE WHEN ($like(utm_source, LikePattern '[%SPS%]') OR $like(utm_source, LikePattern '[%SPMS%]') OR (utm_medium = varchar 'affiliate')) THEN varchar(9) 'Cross LOB' ELSE varchar(9) 'Same LOB' END) │ expr_1309 := (CASE WHEN (expr_535 IN (varchar 'buy_request', varchar 'buyrequest')) THEN varchar 'buyrequest' WHEN (expr_535 IN (varchar 'car_finance', varchar 'carfinance')) THEN varchar 'carfinance' WHEN $like(lower(expr_535), LikePattern '[%callback%]') THEN varchar 'callback' WHEN (expr_535 IN (varchar 'contact_us', varchar 'contactus')) THEN varchar 'contactus' WHEN (expr_535 IN (varchar 'deal_requested', varchar 'dealrequest')) THEN varchar 'dealrequest' WHEN $like(lower(expr_535), LikePattern '[%direct%]') THEN varchar 'direct' WHEN $like(lower(expr_535), LikePattern '[%facebookleadform%]') THEN varchar 'facebookleadform' WHEN $like(lower(expr_535), LikePattern '[%filters%]') THEN varchar 'neutralpage' WHEN $like(lower(expr_535), LikePattern '[%neutral%]') THEN varchar 'neutralpage' WHEN (expr_535 IN (varchar 'filters', varchar 'neutral_page')) THEN varchar 'neutralpage' WHEN $like(lower(expr_535), LikePattern '[%googleleadform%]') THEN varchar 'googleleadform' WHEN $like(lower(expr_535), LikePattern '[%lead%]') THEN varchar 'lead' WHEN (expr_535 IN (varchar 'message', varchar 'whatsapp')) THEN varchar 'message' WHEN (expr_535 IN (varchar 'notify_me', varchar 'notifyme')) THEN varchar 'notifyme' WHEN $like(lower(expr_535), LikePattern '[%proxycontextmodel%]') THEN varchar 'proxycontextmodel' WHEN $like(lower(expr_535), LikePattern '[%reference%]') THEN varchar 'reference' WHEN $like(lower(expr_535), LikePattern '[%sell_to_buy_lead%]') THEN varchar 'lead' WHEN $like(lower(expr_535), LikePattern '[%shortlist%]') THEN varchar 'shortlist' WHEN (expr_535 IN (varchar 'viewinspectionreport', varchar 'view_inspection_report')) THEN varchar 'viewinspectionreport' WHEN $like(lower(expr_535), LikePattern '[%webarticle%]') THEN varchar 'webarticle' WHEN (expr_535 IN (varchar 'PDP_PhotoGallery_360', varchar 'PDP_PhotoGallery_AllPhotos')) THEN varchar 'imagegallery' WHEN ((expr_535 = varchar 'user_activity_log') AND (user_activity_type = varchar 'view_inspection_report')) THEN varchar 'viewinspectionreport' WHEN ((expr_535 = varchar 'user_activity_log') AND (user_activity_type = varchar 'view_more_car_images')) THEN varchar 'imagegallery' WHEN (expr_535 IS NULL) THEN varchar 'null' ELSE expr_535 END) └─ LeftJoin[criteria = (expr_1304 = expr_1305), distribution = PARTITIONED] │ Layout: [id_4:integer, user_activity_type:varchar, expr_532:date, expr_533:varchar(6), expr_534:unknown, expr_535:varchar, utm_source:varchar, utm_medium:varchar, utm_term:varchar, expr_536:varchar(3), expr_538:varchar, expr_539:varchar(12), expr_540:varchar(7), id_611:integer, expr_1303:varchar(14)] │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} │ Distribution: PARTITIONED │ maySkipOutputDuplicates = true ├─ RemoteSource[sourceFragmentIds = [3]] │ Layout: [id_4:integer, user_activity_type:varchar, expr_532:date, expr_533:varchar(6), expr_534:unknown, expr_535:varchar, utm_source:varchar, utm_medium:varchar, utm_term:varchar, expr_536:varchar(3), expr_538:varchar, expr_539:varchar(12), expr_540:varchar(7), expr_1304:varchar] └─ LocalExchange[partitioning = HASH, arguments = [expr_1305::varchar]] │ Layout: [id_611:integer, expr_1303:varchar(14), expr_1305:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [52]] Layout: [id_611:integer, expr_1303:varchar(14), expr_1305:varchar] Fragment 3 [HASH] Output layout: [id_4, user_activity_type, expr_532, expr_533, expr_534, expr_535, utm_source, utm_medium, utm_term, expr_536, expr_538, expr_539, expr_540, expr_1304] Output partitioning: HASH [expr_1304] Project[] │ Layout: [id_4:integer, user_activity_type:varchar, expr_532:date, expr_533:varchar(6), expr_534:unknown, expr_535:varchar, utm_source:varchar, utm_medium:varchar, utm_term:varchar, expr_536:varchar(3), expr_538:varchar, expr_539:varchar(12), expr_540:varchar(7), expr_1304:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ expr_540 := (CASE WHEN (expr_192 = varchar 'hub') THEN varchar(7) 'hub' WHEN (expr_192 IN (varchar 'Olx', varchar 'CarDekho', varchar 'CarTrade')) THEN varchar(7) 'Offline' ELSE varchar(7) 'Online' END) │ expr_1304 := CAST(id_4 AS varchar) └─ Project[] │ Layout: [id_4:integer, user_activity_type:varchar, expr_532:date, expr_533:varchar(6), expr_534:unknown, expr_192:varchar, expr_535:varchar, utm_source:varchar, utm_medium:varchar, utm_term:varchar, expr_536:varchar(3), expr_538:varchar, expr_539:varchar(12)] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ Aggregate[keys = [id, id_4, user_activity_type, expr_531, expr_532, no_of_testdrives, display_name_472, expr_533, expr_534, expr_192, expr_535, utm_source, utm_medium, utm_term, expr_536, expr_537, registration_no, row_number_530, expr_538, expr_539]] │ Layout: [id:integer, id_4:integer, user_activity_type:varchar, expr_531:bigint, expr_532:date, no_of_testdrives:integer, display_name_472:varchar, expr_533:varchar(6), expr_534:unknown, expr_192:varchar, expr_535:varchar, utm_source:varchar, utm_medium:varchar, utm_term:varchar, expr_536:varchar(3), expr_537:varchar(18), registration_no:varchar, row_number_530:bigint, expr_538:varchar, expr_539:varchar(12)] │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} └─ FilterProject[filterPredicate = (CAST($operator$add(visit_start_time, interval day to second '0 05:30:00.000') AS date) >= date '2024-03-12')] │ Layout: [id_4:integer, id:integer, no_of_testdrives:integer, expr_192:varchar, utm_medium:varchar, utm_source:varchar, utm_term:varchar, user_activity_type:varchar, display_name_472:varchar, registration_no:varchar, row_number_530:bigint, expr_531:bigint, expr_532:date, expr_533:varchar(6), expr_534:unknown, expr_535:varchar, expr_536:varchar(3), expr_537:varchar(18), expr_538:varchar, expr_539:varchar(12)] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B}/{rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ expr_531 := day(CAST($operator$add(visit_start_time, interval day to second '0 05:30:00.000') AS date)) │ expr_532 := CAST($operator$add(visit_start_time, interval day to second '0 05:30:00.000') AS date) │ expr_533 := (CASE WHEN $like(platform_source, LikePattern '[%app%]') THEN varchar(6) 'App' WHEN $like(platform_source, LikePattern '[%web%]') THEN varchar(6) 'Web' WHEN $like(platform_source, LikePattern '[%mweb%]') THEN varchar(6) 'Web' ELSE varchar(6) 'Others' END) │ expr_534 := null::unknown │ expr_535 := (CASE WHEN (NOT (cta_slug IS NULL)) THEN cta_slug ELSE (CASE WHEN (sub_source = varchar 'neutral_page') THEN varchar 'neutral_page' ELSE expr_192 END) END) │ expr_536 := (CASE WHEN (at_home = integer '1') THEN varchar(3) 'HTD' ELSE varchar(3) 'HV' END) │ expr_537 := (CASE WHEN (tag_status = varchar 'available') THEN varchar(18) 'Available' WHEN (tag_status = varchar 'available-&-booked') THEN varchar(18) 'Booked' WHEN (tag_status = varchar 'available-&-in-refurb') THEN varchar(18) 'In refurb' WHEN (tag_status = varchar 'available-&-booked-&-in-refurb') THEN varchar(18) 'Booked & In Refurb' WHEN (tag_status = varchar 'booked') THEN varchar(18) 'Booked' WHEN (tag_status = varchar 'in-refurb') THEN varchar(18) 'In Refurb' WHEN (tag_status = varchar 'upcoming-supply') THEN varchar(18) 'Upcoming Supply' WHEN (tag_status = varchar 'sold') THEN varchar(18) 'Sold' ELSE null::varchar(18) END) │ expr_538 := (CASE WHEN $like(display_name_472, LikePattern '[%Delhi%]') THEN varchar 'NCR' WHEN $like(display_name_472, LikePattern '[%Bangalore%]') THEN varchar 'Bangalore' WHEN $like(display_name_472, LikePattern '[%Hyderabad%]') THEN varchar 'Hyderabad' WHEN $like(display_name_472, LikePattern '[%Gurgaon%]') THEN varchar 'NCR' WHEN $like(display_name_472, LikePattern '[%Punee%]') THEN varchar 'Pune' WHEN $like(display_name_472, LikePattern '[%Mumbai%]') THEN varchar 'Mumbai' WHEN $like(display_name_472, LikePattern '[%Delhi/Delhi NCR%]') THEN varchar 'NCR' WHEN $like(display_name_472, LikePattern '[%Ahmedabad%]') THEN varchar 'Ahmedabad' WHEN $like(display_name_472, LikePattern '[%Noida%]') THEN varchar 'NCR' WHEN $like(display_name_472, LikePattern '[%Chennai%]') THEN varchar 'Chennai' WHEN $like(display_name_472, LikePattern '[%Lucknow%]') THEN varchar 'Lucknow' WHEN $like(display_name_472, LikePattern '[%Kolkata%]') THEN varchar 'Kolkata' WHEN $like(display_name_472, LikePattern '[%Ghaziabad%]') THEN varchar 'NCR' WHEN $like(display_name_472, LikePattern '[%Faridabad%]') THEN varchar 'NCR' WHEN $like(display_name_472, LikePattern '[%Jaipur%]') THEN varchar 'Jaipur' WHEN $like(display_name_472, LikePattern '[%Indore%]') THEN varchar 'Indore' WHEN $like(display_name_472, LikePattern '[%Mysore%]') THEN varchar 'Bangalore' WHEN $like(display_name_472, LikePattern '[%Coimbatore%]') THEN varchar 'Coimbatore' WHEN $like(display_name_472, LikePattern '[%Chandigarh%]') THEN varchar 'Chandigarh' WHEN $like(display_name_472, LikePattern '[%Rewari%]') THEN varchar 'NCR' WHEN $like(display_name_472, LikePattern '[%Ambala%]') THEN varchar 'Chandigarh' WHEN $like(display_name_472, LikePattern '[%Hubli%]') THEN varchar 'Bangalore' WHEN $like(display_name_472, LikePattern '[%Panipat%]') THEN varchar 'NCR' WHEN $like(display_name_472, LikePattern '[%Greater Noida%]') THEN varchar 'NCR' WHEN $like(display_name_472, LikePattern '[%Rohtak%]') THEN varchar 'NCR' WHEN $like(display_name_472, LikePattern '[%Meerut%]') THEN varchar 'NCR' WHEN $like(display_name_472, LikePattern '[%Karnal%]') THEN varchar 'NCR' WHEN $like(display_name_472, LikePattern '[%Sonipat%]') THEN varchar 'NCR' WHEN $like(display_name_472, LikePattern '[%Kanpur%]') THEN varchar 'Lucknow' WHEN $like(display_name_472, LikePattern '[%Mangalore%]') THEN varchar 'Bangalore' WHEN $like(display_name_472, LikePattern '[%Surat%]') THEN varchar 'Surat' WHEN $like(display_name_472, LikePattern '[%Aligarh%]') THEN varchar 'NCR' WHEN $like(display_name_472, LikePattern '[%Belgaum%]') THEN varchar 'Bangalore' WHEN $like(display_name_472, LikePattern '[%Hassan%]') THEN varchar 'Bangalore' WHEN $like(display_name_472, LikePattern '[%Jammu%]') THEN varchar 'NCR' WHEN $like(display_name_472, LikePattern '[%Jhajjar%]') THEN varchar 'NCR' WHEN $like(display_name_472, LikePattern '[%Agra%]') THEN varchar 'NCR' WHEN $like(display_name_472, LikePattern '[%Bhiwadi%]') THEN varchar 'Jaipur' WHEN $like(display_name_472, LikePattern '[%Kolar%]') THEN varchar 'Bangalore' WHEN $like(display_name_472, LikePattern '[%Gulbarga%]') THEN varchar 'Bangalore' WHEN $like(display_name_472, LikePattern '[%Warangal%]') THEN varchar 'Hyderabad' WHEN $like(display_name_472, LikePattern '[%Raichur%]') THEN varchar 'Bangalore' WHEN $like(display_name_472, LikePattern '[%Alwar%]') THEN varchar 'NCR' WHEN $like(display_name_472, LikePattern '[%Nashik%]') THEN varchar 'Pune' WHEN $like(display_name_472, LikePattern '[%Bahadurgarh%]') THEN varchar 'NCR' WHEN $like(display_name_472, LikePattern '[%Mathura%]') THEN varchar 'NCR' WHEN $like(display_name_472, LikePattern '[%Sirsa%]') THEN varchar 'Chandigarh' WHEN $like(display_name_472, LikePattern '[%Thane%]') THEN varchar 'Mumbai' WHEN $like(display_name_472, LikePattern '[%Nagpur%]') THEN varchar 'Pune' WHEN $like(display_name_472, LikePattern '[%Moradabad%]') THEN varchar 'Lucknow' WHEN $like(display_name_472, LikePattern '[%Karimnagar%]') THEN varchar 'Hyderabad' WHEN $like(display_name_472, LikePattern '[%Amritsar%]') THEN varchar 'Chandigarh' WHEN $like(display_name_472, LikePattern '[%Patna%]') THEN varchar 'Lucknow' WHEN $like(display_name_472, LikePattern '[%Bagalkot%]') THEN varchar 'Bangalore' WHEN $like(display_name_472, LikePattern '[%Kochi%]') THEN varchar 'Kochi' WHEN $like(display_name_472, LikePattern '[%Jhansi%]') THEN varchar 'Lucknow' WHEN $like(display_name_472, LikePattern '[%Nizamabad%]') THEN varchar 'Hyderabad' WHEN $like(display_name_472, LikePattern '[%Bareilly%]') THEN varchar 'Lucknow' WHEN $like(display_name_472, LikePattern '[%Saharanpur%]') THEN varchar 'Lucknow' WHEN $like(display_name_472, LikePattern '[%Navi Mumbai%]') THEN varchar 'Mumbai' WHEN $like(display_name_472, LikePattern '[%Jodhpur%]') THEN varchar 'Jaipur' WHEN $like(display_name_472, LikePattern '[%Gwalior%]') THEN varchar 'Indore' WHEN $like(display_name_472, LikePattern '[%Hapur%]') THEN varchar 'NCR' WHEN $like(display_name_472, LikePattern '[%Bhopal%]') THEN varchar 'Indore' WHEN $like(display_name_472, LikePattern '[%Dehradun%]') THEN varchar 'NCR' WHEN $like(display_name_472, LikePattern '[%Kurukshetra%]') THEN varchar 'Chandigarh' WHEN $like(display_name_472, LikePattern '[%Ahmednagar%]') THEN varchar 'Pune' WHEN $like(display_name_472, LikePattern '[%Mandya%]') THEN varchar 'Bangalore' WHEN $like(display_name_472, LikePattern '[%Aurangabad%]') THEN varchar 'Pune' WHEN $like(display_name_472, LikePattern '[%Jalandhar%]') THEN varchar 'Chandigarh' WHEN $like(display_name_472, LikePattern '[%Gorakhpur%]') THEN varchar 'Lucknow' WHEN $like(display_name_472, LikePattern '[%Khammam%]') THEN varchar 'Hyderabad' WHEN $like(display_name_472, LikePattern '[%Muzaffarnagar%]') THEN varchar 'NCR' WHEN $like(display_name_472, LikePattern '[%Rajkot%]') THEN varchar 'Ahmedabad' WHEN $like(display_name_472, LikePattern '[%Varanasi%]') THEN varchar 'Lucknow' WHEN $like(display_name_472, LikePattern '[%Hosur%]') THEN varchar 'Coimbatore' WHEN $like(display_name_472, LikePattern '[%Allahabad%]') THEN varchar 'Lucknow' WHEN $like(display_name_472, LikePattern '[%Bathinda%]') THEN varchar 'Chandigarh' WHEN $like(display_name_472, LikePattern '[%Solapur%]') THEN varchar 'Pune' WHEN $like(display_name_472, LikePattern '[%Vadodara%]') THEN varchar 'Ahmedabad' WHEN $like(display_name_472, LikePattern '[%tumkur%]') THEN varchar 'Bangalore' WHEN $like(display_name_472, LikePattern '[%tumakuru%]') THEN varchar 'Bangalore' WHEN $like(display_name_472, LikePattern '[%shimoga%]') THEN varchar 'Bangalore' WHEN $like(display_name_472, LikePattern '[%Shivamogga%]') THEN varchar 'Bangalore' WHEN $like(display_name_472, LikePattern '[%Navi Mumbai%]') THEN varchar 'Mumbai' WHEN $like(display_name_472, LikePattern '[%Navsari%]') THEN varchar 'Ahmedabad' WHEN $like(display_name_472, LikePattern '[%Pune%]') THEN varchar 'Pune' WHEN $like(display_name_472, LikePattern '[%sangli%]') THEN varchar 'Pune' WHEN $like(display_name_472, LikePattern '[%Bhavnagar%]') THEN varchar 'Ahmedabad' WHEN $like(display_name_472, LikePattern '[%Surat%]') THEN varchar 'Surat' ELSE display_name_472 END) │ expr_539 := (CASE WHEN (NOT (full_name IS NULL)) THEN varchar(12) 'Assigned' ELSE varchar(12) 'Not_Assigned' END) └─ TopNRanking[partitionBy = [id_4], orderBy = [visit_start_time ASC NULLS LAST], limit = 1] │ Layout: [at_home:integer, id_4:integer, id:integer, no_of_testdrives:integer, visit_start_time:timestamp(6) with time zone, platform_source:varchar, sub_source:varchar, full_name:varchar, expr_192:varchar, cta_slug:varchar, utm_medium:varchar, utm_source:varchar, utm_term:varchar, user_activity_type:varchar, display_name_472:varchar, tag_status:varchar, registration_no:varchar, row_number_530:bigint] │ row_number_530 := ROW_NUMBER └─ LocalExchange[partitioning = HASH, arguments = [id_4::integer]] │ Layout: [at_home:integer, id_4:integer, id:integer, no_of_testdrives:integer, visit_start_time:timestamp(6) with time zone, platform_source:varchar, sub_source:varchar, full_name:varchar, expr_192:varchar, cta_slug:varchar, utm_medium:varchar, utm_source:varchar, utm_term:varchar, user_activity_type:varchar, display_name_472:varchar, tag_status:varchar, registration_no:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [4]] Layout: [at_home:integer, id_4:integer, id:integer, no_of_testdrives:integer, visit_start_time:timestamp(6) with time zone, platform_source:varchar, sub_source:varchar, full_name:varchar, expr_192:varchar, cta_slug:varchar, utm_medium:varchar, utm_source:varchar, utm_term:varchar, user_activity_type:varchar, display_name_472:varchar, tag_status:varchar, registration_no:varchar] Fragment 4 [HASH] Output layout: [at_home, id_4, id, no_of_testdrives, visit_start_time, platform_source, sub_source, full_name, expr_192, cta_slug, utm_medium, utm_source, utm_term, user_activity_type, display_name_472, tag_status, registration_no] Output partitioning: HASH [id_4] TopNRanking[partitionBy = [id_4], orderBy = [visit_start_time ASC NULLS LAST], limit = 1] │ Layout: [at_home:integer, id_4:integer, id:integer, no_of_testdrives:integer, visit_start_time:timestamp(6) with time zone, platform_source:varchar, sub_source:varchar, full_name:varchar, expr_192:varchar, cta_slug:varchar, utm_medium:varchar, utm_source:varchar, utm_term:varchar, user_activity_type:varchar, display_name_472:varchar, tag_status:varchar, registration_no:varchar] │ row_number_530 := ROW_NUMBER └─ InnerJoin[criteria = (status_id = id_525), filter = (CAST($operator$add(visit_start_time, interval day to second '0 05:30:00.000') AS date) >= date '2024-01-01'), distribution = REPLICATED] │ Layout: [at_home:integer, id_4:integer, id:integer, no_of_testdrives:integer, visit_start_time:timestamp(6) with time zone, platform_source:varchar, sub_source:varchar, full_name:varchar, expr_192:varchar, cta_slug:varchar, utm_medium:varchar, utm_source:varchar, utm_term:varchar, user_activity_type:varchar, display_name_472:varchar, tag_status:varchar, registration_no:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} │ Distribution: REPLICATED │ dynamicFilterAssignments = {id_525 -> #df_17246} ├─ LeftJoin[criteria = (profile_id = id_514), distribution = PARTITIONED] │ │ Layout: [at_home:integer, id_4:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone, platform_source:varchar, sub_source:varchar, full_name:varchar, expr_192:varchar, cta_slug:varchar, utm_medium:varchar, utm_source:varchar, utm_term:varchar, user_activity_type:varchar, display_name_472:varchar, tag_status:varchar, registration_no:varchar] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 513.68MB, network: 0B} │ │ Distribution: PARTITIONED │ ├─ RemoteSource[sourceFragmentIds = [5]] │ │ Layout: [at_home:integer, id_4:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone, platform_source:varchar, sub_source:varchar, full_name:varchar, expr_192:varchar, cta_slug:varchar, utm_medium:varchar, utm_source:varchar, utm_term:varchar, user_activity_type:varchar, display_name_472:varchar, profile_id:integer, tag_status:varchar] │ └─ LocalExchange[partitioning = HASH, arguments = [id_514::integer]] │ │ Layout: [id_514:integer, registration_no:varchar] │ │ Estimates: {rows: 26793658 (513.68MB), cpu: 513.68M, memory: 0B, network: 0B} │ └─ RemoteSource[sourceFragmentIds = [50]] │ Layout: [id_514:integer, registration_no:varchar] └─ LocalExchange[partitioning = SINGLE] │ Layout: [id_525:integer] │ Estimates: {rows: ? (?), cpu: 0, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [51]] Layout: [id_525:integer] Fragment 5 [HASH] Output layout: [at_home, id_4, id, no_of_testdrives, status_id, visit_start_time, platform_source, sub_source, full_name, expr_192, cta_slug, utm_medium, utm_source, utm_term, user_activity_type, display_name_472, profile_id, tag_status] Output partitioning: HASH [profile_id] LeftJoin[criteria = (sell_lead_id_484 = id_496), distribution = PARTITIONED] │ Layout: [at_home:integer, id_4:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone, platform_source:varchar, sub_source:varchar, full_name:varchar, expr_192:varchar, cta_slug:varchar, utm_medium:varchar, utm_source:varchar, utm_term:varchar, user_activity_type:varchar, display_name_472:varchar, profile_id:integer, tag_status:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 210.65MB, network: 0B} │ Distribution: PARTITIONED ├─ RemoteSource[sourceFragmentIds = [6]] │ Layout: [at_home:integer, id_4:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone, platform_source:varchar, sub_source:varchar, full_name:varchar, expr_192:varchar, cta_slug:varchar, utm_medium:varchar, utm_source:varchar, utm_term:varchar, user_activity_type:varchar, display_name_472:varchar, sell_lead_id_484:integer] └─ LocalExchange[partitioning = HASH, arguments = [id_496::integer]] │ Layout: [id_496:integer, profile_id:integer, tag_status:varchar] │ Estimates: {rows: 14393538 (210.65MB), cpu: 210.65M, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [49]] Layout: [id_496:integer, profile_id:integer, tag_status:varchar] Fragment 6 [HASH] Output layout: [at_home, id_4, id, no_of_testdrives, status_id, visit_start_time, platform_source, sub_source, full_name, expr_192, cta_slug, utm_medium, utm_source, utm_term, user_activity_type, display_name_472, sell_lead_id_484] Output partitioning: HASH [sell_lead_id_484] LeftJoin[criteria = (id = visit_id), distribution = REPLICATED] │ Layout: [at_home:integer, id_4:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone, platform_source:varchar, sub_source:varchar, full_name:varchar, expr_192:varchar, cta_slug:varchar, utm_medium:varchar, utm_source:varchar, utm_term:varchar, user_activity_type:varchar, display_name_472:varchar, sell_lead_id_484:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: 178.29MB, network: 0B} │ Distribution: REPLICATED ├─ LeftJoin[criteria = (city_id = id_473), distribution = REPLICATED] │ │ Layout: [at_home:integer, id_4:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone, platform_source:varchar, sub_source:varchar, full_name:varchar, expr_192:varchar, cta_slug:varchar, utm_medium:varchar, utm_source:varchar, utm_term:varchar, user_activity_type:varchar, display_name_472:varchar] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 91.90kB, network: 0B} │ │ Distribution: REPLICATED │ ├─ LeftJoin[criteria = (hub_id = id_465), distribution = REPLICATED] │ │ │ Layout: [at_home:integer, id_4:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone, city_id:integer, platform_source:varchar, sub_source:varchar, full_name:varchar, expr_192:varchar, cta_slug:varchar, utm_medium:varchar, utm_source:varchar, utm_term:varchar, user_activity_type:varchar] │ │ │ Estimates: {rows: ? (?), cpu: ?, memory: 4.13kB, network: 0B} │ │ │ Distribution: REPLICATED │ │ ├─ LeftJoin[criteria = (id_450 = marketing_attribution_id_459), distribution = PARTITIONED] │ │ │ │ Layout: [at_home:integer, id_4:integer, hub_id:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone, city_id:integer, platform_source:varchar, sub_source:varchar, full_name:varchar, expr_192:varchar, cta_slug:varchar, utm_medium:varchar, utm_source:varchar, utm_term:varchar, user_activity_type:varchar] │ │ │ │ Estimates: {rows: ? (?), cpu: ?, memory: 117.48MB, network: 0B} │ │ │ │ Distribution: PARTITIONED │ │ │ ├─ RemoteSource[sourceFragmentIds = [7]] │ │ │ │ Layout: [at_home:integer, id_4:integer, hub_id:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone, city_id:integer, platform_source:varchar, sub_source:varchar, full_name:varchar, expr_192:varchar, cta_slug:varchar, id_450:integer, utm_medium:varchar, utm_source:varchar, utm_term:varchar] │ │ │ └─ LocalExchange[partitioning = HASH, arguments = [marketing_attribution_id_459::integer]] │ │ │ │ Layout: [marketing_attribution_id_459:integer, user_activity_type:varchar] │ │ │ │ Estimates: {rows: 12125080 (117.48MB), cpu: 117.48M, memory: 0B, network: 0B} │ │ │ └─ RemoteSource[sourceFragmentIds = [45]] │ │ │ Layout: [marketing_attribution_id_459:integer, user_activity_type:varchar] │ │ └─ LocalExchange[partitioning = SINGLE] │ │ │ Layout: [id_465:integer] │ │ │ Estimates: {rows: 141 (705B), cpu: 0, memory: 0B, network: 0B} │ │ └─ RemoteSource[sourceFragmentIds = [46]] │ │ Layout: [id_465:integer] │ └─ LocalExchange[partitioning = SINGLE] │ │ Layout: [display_name_472:varchar, id_473:integer] │ │ Estimates: {rows: 454 (15.32kB), cpu: 0, memory: 0B, network: 0B} │ └─ RemoteSource[sourceFragmentIds = [47]] │ Layout: [display_name_472:varchar, id_473:integer] └─ LocalExchange[partitioning = HASH, arguments = [visit_id::integer]] │ Layout: [sell_lead_id_484:integer, visit_id:integer] │ Estimates: {rows: 3116766 (29.72MB), cpu: 29.72M, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [48]] Layout: [sell_lead_id_484:integer, visit_id:integer] Fragment 7 [HASH] Output layout: [at_home, id_4, hub_id, id, no_of_testdrives, status_id, visit_start_time, city_id, platform_source, sub_source, full_name, expr_192, cta_slug, id_450, utm_medium, utm_source, utm_term] Output partitioning: HASH [id_450] LeftJoin[criteria = (expr_447 = id_450), distribution = PARTITIONED] │ Layout: [at_home:integer, id_4:integer, hub_id:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone, city_id:integer, platform_source:varchar, sub_source:varchar, full_name:varchar, expr_192:varchar, cta_slug:varchar, id_450:integer, utm_medium:varchar, utm_source:varchar, utm_term:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 5.05GB, network: 0B} │ Distribution: PARTITIONED ├─ RemoteSource[sourceFragmentIds = [8]] │ Layout: [at_home:integer, id_4:integer, hub_id:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone, city_id:integer, platform_source:varchar, sub_source:varchar, full_name:varchar, expr_192:varchar, cta_slug:varchar, expr_447:integer] └─ LocalExchange[partitioning = HASH, arguments = [id_450::integer]] │ Layout: [id_450:integer, utm_medium:varchar, utm_source:varchar, utm_term:varchar] │ Estimates: {rows: 196944231 (5.05GB), cpu: 5.05G, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [44]] Layout: [id_450:integer, utm_medium:varchar, utm_source:varchar, utm_term:varchar] Fragment 8 [HASH] Output layout: [at_home, id_4, hub_id, id, no_of_testdrives, status_id, visit_start_time, city_id, platform_source, sub_source, full_name, expr_192, cta_slug, expr_447] Output partitioning: HASH [expr_447] LeftJoin[criteria = (id_4 = id_211), distribution = PARTITIONED] │ Layout: [at_home:integer, id_4:integer, hub_id:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone, city_id:integer, platform_source:varchar, sub_source:varchar, full_name:varchar, expr_192:varchar, cta_slug:varchar, expr_447:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} │ Distribution: PARTITIONED ├─ LeftJoin[criteria = (id_4 = id_53), distribution = PARTITIONED] │ │ Layout: [at_home:integer, id_4:integer, hub_id:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone, city_id:integer, platform_source:varchar, sub_source:varchar, full_name:varchar, expr_192:varchar] │ │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} │ │ Distribution: PARTITIONED │ ├─ RemoteSource[sourceFragmentIds = [9]] │ │ Layout: [at_home:integer, id_4:integer, hub_id:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone, city_id:integer, platform_source:varchar, sub_source:varchar, full_name:varchar] │ └─ LocalExchange[partitioning = HASH, arguments = [id_53::integer]] │ │ Layout: [id_53:integer, expr_192:varchar] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ └─ Project[] │ │ Layout: [id_53:integer, expr_192:varchar] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ │ expr_192 := (CASE WHEN (expr = varchar 'www.olx.in') THEN varchar 'Olx' WHEN (expr = varchar 'www.cardekho.com') THEN varchar 'CarDekho' WHEN (expr = varchar 'www.cartrade.com') THEN varchar 'CarTrade' ELSE expr END) │ └─ Project[] │ │ Layout: [id_53:integer, expr:varchar] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ │ expr := (CASE WHEN (source_object_type_id_71 = integer '321') THEN display_name_183 WHEN ((source_object_type_id_71 = integer '246') AND (url_189 = varchar 'Direct')) THEN varchar 'direct' WHEN (source_object_type_id_71 = integer '319') THEN display_name_100 WHEN (source_object_type_id_71 = integer '322') THEN display_name_100 ELSE model END) │ └─ LeftJoin[criteria = (source_object_id_70 = id_188), filter = (source_object_type_id_71 = integer '246'), distribution = REPLICATED] │ │ Layout: [id_53:integer, source_object_type_id_71:integer, model:varchar, display_name_100:varchar, display_name_183:varchar, url_189:varchar] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 6.43MB, network: 0B} │ │ Distribution: REPLICATED │ ├─ LeftJoin[criteria = (id_53 = id_122), distribution = PARTITIONED] │ │ │ Layout: [id_53:integer, source_object_id_70:integer, source_object_type_id_71:integer, model:varchar, display_name_100:varchar, display_name_183:varchar] │ │ │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} │ │ │ Distribution: PARTITIONED │ │ ├─ RemoteSource[sourceFragmentIds = [18]] │ │ │ Layout: [id_53:integer, source_object_id_70:integer, source_object_type_id_71:integer, model:varchar, display_name_100:varchar] │ │ └─ LocalExchange[partitioning = HASH, arguments = [id_122::integer]] │ │ │ Layout: [id_122:integer, display_name_183:varchar] │ │ │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ │ └─ RemoteSource[sourceFragmentIds = [24]] │ │ Layout: [id_122:integer, display_name_183:varchar] │ └─ LocalExchange[partitioning = SINGLE] │ │ Layout: [id_188:integer, url_189:varchar] │ │ Estimates: {rows: 9042 (1.07MB), cpu: 0, memory: 0B, network: 0B} │ └─ RemoteSource[sourceFragmentIds = [29]] │ Layout: [id_188:integer, url_189:varchar] └─ LocalExchange[partitioning = HASH, arguments = [id_211::integer]] │ Layout: [id_211:integer, cta_slug:varchar, expr_447:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ Project[] │ Layout: [id_211:integer, cta_slug:varchar, expr_447:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ expr_447 := (CASE WHEN (id_211 = id_335) THEN min ELSE marketing_attribution_id END) └─ LeftJoin[criteria = (id_211 = id_335), distribution = PARTITIONED] │ Layout: [id_211:integer, marketing_attribution_id:integer, cta_slug:varchar, id_335:integer, min:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} │ Distribution: PARTITIONED ├─ RemoteSource[sourceFragmentIds = [30]] │ Layout: [id_211:integer, marketing_attribution_id:integer, cta_slug:varchar] └─ LocalExchange[partitioning = HASH, arguments = [id_335::integer]] │ Layout: [id_335:integer, min:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [37]] Layout: [id_335:integer, min:integer] Fragment 9 [HASH] Output layout: [at_home, id_4, hub_id, id, no_of_testdrives, status_id, visit_start_time, city_id, platform_source, sub_source, full_name] Output partitioning: HASH [id_4] LeftJoin[criteria = (account_id = account_id_29), distribution = PARTITIONED] │ Layout: [at_home:integer, id_4:integer, hub_id:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone, city_id:integer, platform_source:varchar, sub_source:varchar, full_name:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 582.75MB, network: 0B} │ Distribution: PARTITIONED ├─ RemoteSource[sourceFragmentIds = [10]] │ Layout: [at_home:integer, id_4:integer, hub_id:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone, account_id:integer, city_id:integer, platform_source:varchar, sub_source:varchar, full_name:varchar] └─ LocalExchange[partitioning = HASH, arguments = [account_id_29::integer]] │ Layout: [account_id_29:integer] │ Estimates: {rows: 128100977 (582.75MB), cpu: 582.75M, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [17]] Layout: [account_id_29:integer] Fragment 10 [HASH] Output layout: [at_home, id_4, hub_id, id, no_of_testdrives, status_id, visit_start_time, account_id, city_id, platform_source, sub_source, full_name] Output partitioning: HASH [account_id] LeftJoin[criteria = (assigned_to_id_9 = id_23), distribution = PARTITIONED] │ Layout: [at_home:integer, id_4:integer, hub_id:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone, account_id:integer, city_id:integer, platform_source:varchar, sub_source:varchar, full_name:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 438.19MB, network: 0B} │ Distribution: PARTITIONED ├─ RemoteSource[sourceFragmentIds = [11]] │ Layout: [at_home:integer, id_4:integer, hub_id:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone, account_id:integer, city_id:integer, platform_source:varchar, sub_source:varchar, assigned_to_id_9:integer] └─ LocalExchange[partitioning = HASH, arguments = [id_23::integer]] │ Layout: [full_name:varchar, id_23:integer] │ Estimates: {rows: 17988382 (438.19MB), cpu: 438.19M, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [16]] Layout: [full_name:varchar, id_23:integer] Fragment 11 [HASH] Output layout: [at_home, id_4, hub_id, id, no_of_testdrives, status_id, visit_start_time, account_id, city_id, platform_source, sub_source, assigned_to_id_9] Output partitioning: HASH [assigned_to_id_9] LeftJoin[criteria = (id_4 = context_id_10), distribution = PARTITIONED] │ Layout: [account_id:integer, city_id:integer, platform_source:varchar, sub_source:varchar, id_4:integer, at_home:integer, hub_id:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone, assigned_to_id_9:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} │ Distribution: PARTITIONED ├─ InnerJoin[criteria = (id_4 = context_id), distribution = PARTITIONED] │ │ Layout: [account_id:integer, city_id:integer, id_4:integer, platform_source:varchar, sub_source:varchar, at_home:integer, hub_id:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 101.12MB, network: 0B} │ │ Distribution: PARTITIONED │ │ dynamicFilterAssignments = {context_id -> #df_17247} │ ├─ RemoteSource[sourceFragmentIds = [12]] │ │ Layout: [account_id:integer, city_id:integer, id_4:integer, platform_source:varchar, sub_source:varchar] │ └─ LocalExchange[partitioning = HASH, arguments = [context_id::integer]] │ │ Layout: [at_home:integer, context_id:integer, hub_id:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone] │ │ Estimates: {rows: 2977093 (101.12MB), cpu: 101.12M, memory: 0B, network: 0B} │ └─ RemoteSource[sourceFragmentIds = [13]] │ Layout: [at_home:integer, context_id:integer, hub_id:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone] └─ FilterProject[filterPredicate = (row_number = bigint '1')] │ Layout: [assigned_to_id_9:integer, context_id_10:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B}/{rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ Project[] │ Layout: [assigned_to_id_9:integer, context_id_10:integer, row_number:bigint] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ TopNRanking[partitionBy = [context_id_10], orderBy = [created_time DESC NULLS LAST], limit = 1] │ Layout: [assigned_to_id_9:integer, context_id_10:integer, created_time:timestamp(6) with time zone, row_number:bigint] │ row_number := ROW_NUMBER └─ LocalExchange[partitioning = HASH, arguments = [context_id_10::integer]] │ Layout: [assigned_to_id_9:integer, context_id_10:integer, created_time:timestamp(6) with time zone] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [14]] Layout: [assigned_to_id_9:integer, context_id_10:integer, created_time:timestamp(6) with time zone] Fragment 12 [SOURCE] Output layout: [account_id, city_id, id_4, platform_source, sub_source] Output partitioning: HASH [id_4] ScanFilterProject[table = iceberg:sp_web.buy_lead_buylead$data@1299828741364571249, filterPredicate = (category = varchar 'assured'), dynamicFilters = {id_4 = #df_17247}] Layout: [account_id:integer, city_id:integer, id_4:integer, platform_source:varchar, sub_source:varchar] Estimates: {rows: 12700031 (334.11MB), cpu: 400.56M, memory: 0B, network: 0B}/{rows: 6350016 (167.05MB), cpu: 400.56M, memory: 0B, network: 0B}/{rows: 6350016 (167.05MB), cpu: 167.05M, memory: 0B, network: 0B} category := 8:category:varchar id_4 := 19:id:integer city_id := 9:city_id:integer sub_source := 39:sub_source:varchar platform_source := 28:platform_source:varchar account_id := 1:account_id:integer Fragment 13 [SOURCE] Output layout: [at_home, context_id, hub_id, id, no_of_testdrives, status_id, visit_start_time] Output partitioning: HASH [context_id] ScanFilter[table = iceberg:sp_web.visits_visit$data@918499440402197125, dynamicFilters = {status_id = #df_17246}] Layout: [at_home:integer, context_id:integer, hub_id:integer, id:integer, no_of_testdrives:integer, status_id:integer, visit_start_time:timestamp(6) with time zone] Estimates: {rows: 2977093 (101.12MB), cpu: 101.12M, memory: 0B, network: 0B}/{rows: 2977093 (101.12MB), cpu: 101.12M, memory: 0B, network: 0B} status_id := 36:status_id:integer at_home := 2:at_home:integer no_of_testdrives := 28:no_of_testdrives:integer visit_start_time := 48:visit_start_time:timestamp(6) with time zone context_id := 12:context_id:integer id := 25:id:integer hub_id := 24:hub_id:integer Fragment 14 [SOURCE] Output layout: [assigned_to_id_9, context_id_10, created_time] Output partitioning: HASH [context_id_10] TopNRanking[partitionBy = [context_id_10], orderBy = [created_time DESC NULLS LAST], limit = 1] │ Layout: [assigned_to_id_9:integer, context_id_10:integer, created_time:timestamp(6) with time zone] │ row_number := ROW_NUMBER └─ InnerJoin[criteria = (assigned_to_id_9 = user_id_19), distribution = REPLICATED] │ Layout: [assigned_to_id_9:integer, context_id_10:integer, created_time:timestamp(6) with time zone] │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} │ Distribution: REPLICATED │ dynamicFilterAssignments = {user_id_19 -> #df_17253} ├─ ScanFilter[table = iceberg:sp_web.workflow_usertask$data@2993060954803322895, dynamicFilters = {assigned_to_id_9 = #df_17253}] │ Layout: [assigned_to_id_9:integer, context_id_10:integer, created_time:timestamp(6) with time zone] │ Estimates: {rows: 169318201 (3.56GB), cpu: 3.56G, memory: 0B, network: 0B}/{rows: 169318201 (3.56GB), cpu: 3.56G, memory: 0B, network: 0B} │ context_id_10 := 3:context_id:integer │ created_time := 5:created_time:timestamp(6) with time zone │ assigned_to_id_9 := 2:assigned_to_id:integer └─ LocalExchange[partitioning = SINGLE] │ Layout: [user_id_19:integer] │ Estimates: {rows: ? (?), cpu: 0, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [15]] Layout: [user_id_19:integer] Fragment 15 [SOURCE] Output layout: [user_id_19] Output partitioning: BROADCAST [] ScanFilterProject[table = iceberg:sp_web.spinny_auth_user_groups$data@4640214938704829124, filterPredicate = (group_id IN (integer '132', integer '206'))] Layout: [user_id_19:integer] Estimates: {rows: 30103 (146.99kB), cpu: 293.97k, memory: 0B, network: 0B}/{rows: ? (?), cpu: 293.97k, memory: 0B, network: 0B}/{rows: ? (?), cpu: ?, memory: 0B, network: 0B} group_id := 1:group_id:integer user_id_19 := 4:user_id:integer Fragment 16 [SOURCE] Output layout: [full_name, id_23] Output partitioning: HASH [id_23] TableScan[table = iceberg:sp_web.spinny_auth_user$data@140806201974491105] Layout: [full_name:varchar, id_23:integer] Estimates: {rows: 17988382 (438.19MB), cpu: 438.19M, memory: 0B, network: 0B} full_name := 6:full_name:varchar id_23 := 7:id:integer Fragment 17 [SOURCE] Output layout: [account_id_29] Output partitioning: HASH [account_id_29] TableScan[table = iceberg:sp_phonecall.call_logs$data@138828993269347242] Layout: [account_id_29:integer] Estimates: {rows: 128100977 (582.75MB), cpu: 582.75M, memory: 0B, network: 0B} account_id_29 := 30:account_id:integer Fragment 18 [HASH] Output layout: [id_53, source_object_id_70, source_object_type_id_71, model, display_name_100] Output partitioning: HASH [id_53] LeftJoin[criteria = (platform_id = id_101), filter = (source_object_type_id_71 IN (integer '322', integer '319')), distribution = REPLICATED] │ Layout: [id_53:integer, source_object_id_70:integer, source_object_type_id_71:integer, model:varchar, display_name_100:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 3.22kB, network: 0B} │ Distribution: REPLICATED ├─ LeftJoin[criteria = (source_object_id_70 = id_94), filter = (source_object_type_id_71 IN (integer '322', integer '319')), distribution = PARTITIONED] │ │ Layout: [id_53:integer, source_object_id_70:integer, source_object_type_id_71:integer, model:varchar, platform_id:integer] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 1.09kB, network: 0B} │ │ Distribution: PARTITIONED │ ├─ LeftJoin[criteria = (source_object_id_70 = id_83), distribution = PARTITIONED] │ │ │ Layout: [id_53:integer, source_object_id_70:integer, source_object_type_id_71:integer, model:varchar] │ │ │ Estimates: {rows: ? (?), cpu: ?, memory: 872.63MB, network: 0B} │ │ │ Distribution: PARTITIONED │ │ ├─ RemoteSource[sourceFragmentIds = [19]] │ │ │ Layout: [id_53:integer, source_object_id_70:integer, source_object_type_id_71:integer, model:varchar] │ │ └─ LocalExchange[partitioning = HASH, arguments = [id_83::integer]] │ │ │ Layout: [id_83:integer] │ │ │ Estimates: {rows: 183004002 (872.63MB), cpu: 872.63M, memory: 0B, network: 0B} │ │ └─ RemoteSource[sourceFragmentIds = [21]] │ │ Layout: [id_83:integer] │ └─ LocalExchange[partitioning = SINGLE] │ │ Layout: [id_94:integer, platform_id:integer] │ │ Estimates: {rows: 112 (1.09kB), cpu: 0, memory: 0B, network: 0B} │ └─ RemoteSource[sourceFragmentIds = [22]] │ Layout: [id_94:integer, platform_id:integer] └─ LocalExchange[partitioning = SINGLE] │ Layout: [display_name_100:varchar, id_101:integer] │ Estimates: {rows: 5 (549B), cpu: 0, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [23]] Layout: [display_name_100:varchar, id_101:integer] Fragment 19 [SOURCE] Output layout: [id_53, source_object_id_70, source_object_type_id_71, model] Output partitioning: HASH [source_object_id_70] LeftJoin[criteria = (source_object_type_id_71 = id_78), distribution = REPLICATED] │ Layout: [id_53:integer, source_object_id_70:integer, source_object_type_id_71:integer, model:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 230.45kB, network: 0B} │ Distribution: REPLICATED ├─ ScanFilterProject[table = iceberg:sp_web.buy_lead_buylead$data@1299828741364571249, filterPredicate = (CAST($operator$add(created_on_46, interval day to second '0 05:30:00.000') AS date) >= date '2018-01-30')] │ Layout: [id_53:integer, source_object_id_70:integer, source_object_type_id_71:integer] │ Estimates: {rows: 12700031 (181.61MB), cpu: 339.06M, memory: 0B, network: 0B}/{rows: 6350016 (90.81MB), cpu: 339.06M, memory: 0B, network: 0B}/{rows: 6350016 (90.81MB), cpu: 90.81M, memory: 0B, network: 0B} │ id_53 := 19:id:integer │ source_object_id_70 := 36:source_object_id:integer │ source_object_type_id_71 := 37:source_object_type_id:integer │ created_on_46 := 12:created_on:timestamp(6) with time zone └─ LocalExchange[partitioning = SINGLE] │ Layout: [id_78:integer, model:varchar] │ Estimates: {rows: 1030 (38.41kB), cpu: 0, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [20]] Layout: [id_78:integer, model:varchar] Fragment 20 [SOURCE] Output layout: [id_78, model] Output partitioning: BROADCAST [] TableScan[table = iceberg:sp_web.django_content_type$data@9009429266202918266] Layout: [id_78:integer, model:varchar] Estimates: {rows: 1030 (38.41kB), cpu: 38.41k, memory: 0B, network: 0B} model := 3:model:varchar id_78 := 2:id:integer Fragment 21 [SOURCE] Output layout: [id_83] Output partitioning: HASH [id_83] TableScan[table = iceberg:sp_web.whatsapp_message$data@7433077615325471857] Layout: [id_83:integer] Estimates: {rows: 183004002 (872.63MB), cpu: 872.63M, memory: 0B, network: 0B} id_83 := 4:id:integer Fragment 22 [SOURCE] Output layout: [id_94, platform_id] Output partitioning: HASH [id_94] TableScan[table = iceberg:sp_web.external_listing_listingplatformaccounts$data@6017462594562719178] Layout: [id_94:integer, platform_id:integer] Estimates: {rows: 112 (1.09kB), cpu: 1.09k, memory: 0B, network: 0B} id_94 := 8:id:integer platform_id := 12:platform_id:integer Fragment 23 [SOURCE] Output layout: [display_name_100, id_101] Output partitioning: BROADCAST [] TableScan[table = iceberg:sp_web.external_listing_externallistingplatform$data@3106258827814415296] Layout: [display_name_100:varchar, id_101:integer] Estimates: {rows: 5 (549B), cpu: 549, memory: 0B, network: 0B} display_name_100 := 2:display_name:varchar id_101 := 3:id:integer Fragment 24 [SOURCE] Output layout: [id_122, display_name_183] Output partitioning: HASH [id_122] LeftJoin[criteria = (platform_id_176 = id_184), distribution = REPLICATED] │ Layout: [id_122:integer, display_name_183:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 3.22kB, network: 0B} │ Distribution: REPLICATED ├─ LeftJoin[criteria = (account_id_158 = id_172), distribution = REPLICATED] │ │ Layout: [id_122:integer, platform_id_176:integer] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 6.56kB, network: 0B} │ │ Distribution: REPLICATED │ ├─ LeftJoin[criteria = (listing_id = id_161), distribution = REPLICATED] │ │ │ Layout: [id_122:integer, account_id_158:integer] │ │ │ Estimates: {rows: ? (?), cpu: ?, memory: 3.12MB, network: 0B} │ │ │ Distribution: REPLICATED │ │ ├─ LeftJoin[criteria = (source_object_id_139 = id_152), filter = (source_object_type_id_140 = integer '321'), distribution = REPLICATED] │ │ │ │ Layout: [id_122:integer, listing_id:integer] │ │ │ │ Estimates: {rows: ? (?), cpu: ?, memory: 19.41MB, network: 0B} │ │ │ │ Distribution: REPLICATED │ │ │ ├─ TableScan[table = iceberg:sp_web.buy_lead_buylead$data@1299828741364571249] │ │ │ │ Layout: [id_122:integer, source_object_id_139:integer, source_object_type_id_140:integer] │ │ │ │ Estimates: {rows: 12700031 (181.61MB), cpu: 181.61M, memory: 0B, network: 0B} │ │ │ │ source_object_id_139 := 36:source_object_id:integer │ │ │ │ id_122 := 19:id:integer │ │ │ │ source_object_type_id_140 := 37:source_object_type_id:integer │ │ │ └─ LocalExchange[partitioning = SINGLE] │ │ │ │ Layout: [id_152:integer, listing_id:integer] │ │ │ │ Estimates: {rows: 339234 (3.24MB), cpu: 0, memory: 0B, network: 0B} │ │ │ └─ RemoteSource[sourceFragmentIds = [25]] │ │ │ Layout: [id_152:integer, listing_id:integer] │ │ └─ LocalExchange[partitioning = SINGLE] │ │ │ Layout: [account_id_158:integer, id_161:integer] │ │ │ Estimates: {rows: 54520 (532.42kB), cpu: 0, memory: 0B, network: 0B} │ │ └─ RemoteSource[sourceFragmentIds = [26]] │ │ Layout: [account_id_158:integer, id_161:integer] │ └─ LocalExchange[partitioning = SINGLE] │ │ Layout: [id_172:integer, platform_id_176:integer] │ │ Estimates: {rows: 112 (1.09kB), cpu: 0, memory: 0B, network: 0B} │ └─ RemoteSource[sourceFragmentIds = [27]] │ Layout: [id_172:integer, platform_id_176:integer] └─ LocalExchange[partitioning = SINGLE] │ Layout: [display_name_183:varchar, id_184:integer] │ Estimates: {rows: 5 (549B), cpu: 0, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [28]] Layout: [display_name_183:varchar, id_184:integer] Fragment 25 [SOURCE] Output layout: [id_152, listing_id] Output partitioning: BROADCAST [] TableScan[table = iceberg:sp_web.external_listing_externalbuyrequest$data@8613310664252366845] Layout: [id_152:integer, listing_id:integer] Estimates: {rows: 339234 (3.24MB), cpu: 3.24M, memory: 0B, network: 0B} id_152 := 7:id:integer listing_id := 8:listing_id:integer Fragment 26 [SOURCE] Output layout: [account_id_158, id_161] Output partitioning: BROADCAST [] TableScan[table = iceberg:sp_web.external_listing_externallisting$data@4144789504165051730] Layout: [account_id_158:integer, id_161:integer] Estimates: {rows: 54520 (532.42kB), cpu: 532.42k, memory: 0B, network: 0B} id_161 := 4:id:integer account_id_158 := 1:account_id:integer Fragment 27 [SOURCE] Output layout: [id_172, platform_id_176] Output partitioning: BROADCAST [] TableScan[table = iceberg:sp_web.external_listing_listingplatformaccounts$data@6017462594562719178] Layout: [id_172:integer, platform_id_176:integer] Estimates: {rows: 112 (1.09kB), cpu: 1.09k, memory: 0B, network: 0B} id_172 := 8:id:integer platform_id_176 := 12:platform_id:integer Fragment 28 [SOURCE] Output layout: [display_name_183, id_184] Output partitioning: BROADCAST [] TableScan[table = iceberg:sp_web.external_listing_externallistingplatform$data@3106258827814415296] Layout: [display_name_183:varchar, id_184:integer] Estimates: {rows: 5 (549B), cpu: 549, memory: 0B, network: 0B} id_184 := 3:id:integer display_name_183 := 2:display_name:varchar Fragment 29 [SOURCE] Output layout: [id_188, url_189] Output partitioning: BROADCAST [] TableScan[table = iceberg:sp_web.webresults_webarticle$data@4621341169227520572] Layout: [id_188:integer, url_189:varchar] Estimates: {rows: 9042 (1.07MB), cpu: 1.07M, memory: 0B, network: 0B} id_188 := 3:id:integer url_189 := 5:url:varchar Fragment 30 [HASH] Output layout: [id_211, marketing_attribution_id, cta_slug] Output partitioning: HASH [id_211] Aggregate[type = FINAL, keys = [id_211, marketing_attribution_id, cta_slug]] │ Layout: [id_211:integer, marketing_attribution_id:integer, cta_slug:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} └─ LocalExchange[partitioning = HASH, arguments = [id_211::integer, marketing_attribution_id::integer, cta_slug::varchar]] │ Layout: [id_211:integer, marketing_attribution_id:integer, cta_slug:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [31]] Layout: [id_211:integer, marketing_attribution_id:integer, cta_slug:varchar] Fragment 31 [HASH] Output layout: [id_211, marketing_attribution_id, cta_slug] Output partitioning: HASH [id_211, marketing_attribution_id, cta_slug] Aggregate[type = PARTIAL, keys = [id_211, marketing_attribution_id, cta_slug]] │ Layout: [id_211:integer, marketing_attribution_id:integer, cta_slug:varchar] └─ FilterProject[filterPredicate = (row_number_316 = bigint '1')] │ Layout: [id_211:integer, cta_slug:varchar, marketing_attribution_id:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B}/{rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ Project[] │ Layout: [id_211:integer, cta_slug:varchar, marketing_attribution_id:integer, row_number_316:bigint] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ TopNRanking[partitionBy = [buy_lead_id_237], orderBy = [log_creation_time ASC NULLS LAST], limit = 1] │ Layout: [id_211:integer, buy_lead_id_237:integer, cta_slug:varchar, log_creation_time:timestamp(6) with time zone, marketing_attribution_id:integer, row_number_316:bigint] │ row_number_316 := ROW_NUMBER └─ LocalExchange[partitioning = HASH, arguments = [buy_lead_id_237::integer]] │ Layout: [id_211:integer, buy_lead_id_237:integer, cta_slug:varchar, log_creation_time:timestamp(6) with time zone, marketing_attribution_id:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [32]] Layout: [id_211:integer, buy_lead_id_237:integer, cta_slug:varchar, log_creation_time:timestamp(6) with time zone, marketing_attribution_id:integer] Fragment 32 [HASH] Output layout: [id_211, buy_lead_id_237, cta_slug, log_creation_time, marketing_attribution_id] Output partitioning: HASH [buy_lead_id_237] TopNRanking[partitionBy = [buy_lead_id_237], orderBy = [log_creation_time ASC NULLS LAST], limit = 1] │ Layout: [id_211:integer, buy_lead_id_237:integer, cta_slug:varchar, log_creation_time:timestamp(6) with time zone, marketing_attribution_id:integer] │ row_number_316 := ROW_NUMBER └─ LeftJoin[criteria = (created_by_id_254 = id_299), distribution = REPLICATED] │ Layout: [id_211:integer, buy_lead_id_237:integer, cta_slug:varchar, log_creation_time:timestamp(6) with time zone, marketing_attribution_id:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: 514.65MB, network: 0B} │ Distribution: REPLICATED ├─ LeftJoin[criteria = (id_211 = context_id_252), distribution = PARTITIONED] │ │ Layout: [buy_lead_id_237:integer, cta_slug:varchar, log_creation_time:timestamp(6) with time zone, marketing_attribution_id:integer, id_211:integer, created_by_id_254:integer] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 28.39MB, network: 0B} │ │ Distribution: PARTITIONED │ ├─ RightJoin[criteria = (buy_lead_id_237 = id_211), distribution = PARTITIONED] │ │ │ Layout: [buy_lead_id_237:integer, cta_slug:varchar, log_creation_time:timestamp(6) with time zone, marketing_attribution_id:integer, id_211:integer] │ │ │ Estimates: {rows: ? (?), cpu: ?, memory: 60.56MB, network: 0B} │ │ │ Distribution: PARTITIONED │ │ │ dynamicFilterAssignments = {id_211 -> #df_17287} │ │ ├─ RemoteSource[sourceFragmentIds = [33]] │ │ │ Layout: [buy_lead_id_237:integer, cta_slug:varchar, log_creation_time:timestamp(6) with time zone, marketing_attribution_id:integer] │ │ └─ LocalExchange[partitioning = HASH, arguments = [id_211::integer]] │ │ │ Layout: [id_211:integer] │ │ │ Estimates: {rows: 12700031 (60.56MB), cpu: 60.56M, memory: 0B, network: 0B} │ │ └─ RemoteSource[sourceFragmentIds = [34]] │ │ Layout: [id_211:integer] │ └─ LocalExchange[partitioning = HASH, arguments = [context_id_252::integer]] │ │ Layout: [context_id_252:integer, created_by_id_254:integer] │ │ Estimates: {rows: 2977093 (28.39MB), cpu: 28.39M, memory: 0B, network: 0B} │ └─ RemoteSource[sourceFragmentIds = [35]] │ Layout: [context_id_252:integer, created_by_id_254:integer] └─ LocalExchange[partitioning = HASH, arguments = [id_299::integer]] │ Layout: [id_299:integer] │ Estimates: {rows: 17988382 (85.78MB), cpu: 85.78M, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [36]] Layout: [id_299:integer] Fragment 33 [SOURCE] Output layout: [buy_lead_id_237, cta_slug, log_creation_time, marketing_attribution_id] Output partitioning: HASH [buy_lead_id_237] ScanFilter[table = iceberg:mongo_marketing_attribution.buy_lead_cta_logs$data@6164463033804556162, dynamicFilters = {buy_lead_id_237 = #df_17287}] Layout: [buy_lead_id_237:integer, cta_slug:varchar, log_creation_time:timestamp(6) with time zone, marketing_attribution_id:integer] Estimates: {rows: 28811712 (802.69MB), cpu: 802.69M, memory: 0B, network: 0B}/{rows: 28811712 (802.69MB), cpu: 802.69M, memory: 0B, network: 0B} log_creation_time := 6:log_creation_time:timestamp(6) with time zone cta_slug := 5:cta_slug:varchar buy_lead_id_237 := 2:buy_lead_id:integer marketing_attribution_id := 7:marketing_attribution_id:integer Fragment 34 [SOURCE] Output layout: [id_211] Output partitioning: HASH [id_211] TableScan[table = iceberg:sp_web.buy_lead_buylead$data@1299828741364571249] Layout: [id_211:integer] Estimates: {rows: 12700031 (60.56MB), cpu: 60.56M, memory: 0B, network: 0B} id_211 := 19:id:integer Fragment 35 [SOURCE] Output layout: [context_id_252, created_by_id_254] Output partitioning: HASH [context_id_252] TableScan[table = iceberg:sp_web.visits_visit$data@918499440402197125] Layout: [context_id_252:integer, created_by_id_254:integer] Estimates: {rows: 2977093 (28.39MB), cpu: 28.39M, memory: 0B, network: 0B} context_id_252 := 12:context_id:integer created_by_id_254 := 14:created_by_id:integer Fragment 36 [SOURCE] Output layout: [id_299] Output partitioning: BROADCAST [] TableScan[table = iceberg:sp_web.spinny_auth_user$data@140806201974491105] Layout: [id_299:integer] Estimates: {rows: 17988382 (85.78MB), cpu: 85.78M, memory: 0B, network: 0B} id_299 := 7:id:integer Fragment 37 [HASH] Output layout: [id_335, min] Output partitioning: HASH [id_335] Project[] │ Layout: [id_335:integer, min:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ Aggregate[type = FINAL, keys = [id_335, cta_slug_364]] │ Layout: [id_335:integer, cta_slug_364:varchar, min:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} │ min := min(min_1314) └─ LocalExchange[partitioning = HASH, arguments = [id_335::integer, cta_slug_364::varchar]] │ Layout: [id_335:integer, cta_slug_364:varchar, min_1314:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [38]] Layout: [id_335:integer, cta_slug_364:varchar, min_1314:integer] Fragment 38 [HASH] Output layout: [id_335, cta_slug_364, min_1314] Output partitioning: HASH [id_335, cta_slug_364] Aggregate[type = PARTIAL, keys = [id_335, cta_slug_364]] │ Layout: [id_335:integer, cta_slug_364:varchar, min_1314:integer] │ min_1314 := min(marketing_attribution_id_366) └─ FilterProject[filterPredicate = ((CASE WHEN ((visit_type_id_419 = integer '2') AND (category_324 = varchar 'assured') AND (is_staff_432 = integer '0') AND (cta_slug_364 = varchar 'buy_request')) THEN integer '1' ELSE integer '0' END) = integer '1')] │ Layout: [id_335:integer, cta_slug_364:varchar, marketing_attribution_id_366:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B}/{rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ LeftJoin[criteria = (created_by_id_383 = id_428), distribution = PARTITIONED] │ Layout: [category_324:varchar, id_335:integer, cta_slug_364:varchar, marketing_attribution_id_366:integer, visit_type_id_419:integer, is_staff_432:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: 171.55MB, network: 0B} │ Distribution: PARTITIONED ├─ RemoteSource[sourceFragmentIds = [39]] │ Layout: [category_324:varchar, id_335:integer, cta_slug_364:varchar, marketing_attribution_id_366:integer, created_by_id_383:integer, visit_type_id_419:integer] └─ LocalExchange[partitioning = HASH, arguments = [id_428::integer]] │ Layout: [id_428:integer, is_staff_432:integer] │ Estimates: {rows: 17988382 (171.55MB), cpu: 171.55M, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [43]] Layout: [id_428:integer, is_staff_432:integer] Fragment 39 [HASH] Output layout: [category_324, id_335, cta_slug_364, marketing_attribution_id_366, created_by_id_383, visit_type_id_419] Output partitioning: HASH [created_by_id_383] LeftJoin[criteria = (id_335 = context_id_381), distribution = PARTITIONED] │ Layout: [cta_slug_364:varchar, marketing_attribution_id_366:integer, category_324:varchar, id_335:integer, created_by_id_383:integer, visit_type_id_419:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: 42.59MB, network: 0B} │ Distribution: PARTITIONED ├─ RightJoin[criteria = (buy_lead_id_361 = id_335), distribution = PARTITIONED] │ │ Layout: [cta_slug_364:varchar, marketing_attribution_id_366:integer, category_324:varchar, id_335:integer] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 127.01MB, network: 0B} │ │ Distribution: PARTITIONED │ │ dynamicFilterAssignments = {id_335 -> #df_17298} │ ├─ RemoteSource[sourceFragmentIds = [40]] │ │ Layout: [buy_lead_id_361:integer, cta_slug_364:varchar, marketing_attribution_id_366:integer] │ └─ LocalExchange[partitioning = HASH, arguments = [id_335::integer]] │ │ Layout: [category_324:varchar, id_335:integer] │ │ Estimates: {rows: 12700031 (127.01MB), cpu: 127.01M, memory: 0B, network: 0B} │ └─ RemoteSource[sourceFragmentIds = [41]] │ Layout: [category_324:varchar, id_335:integer] └─ LocalExchange[partitioning = HASH, arguments = [context_id_381::integer]] │ Layout: [context_id_381:integer, created_by_id_383:integer, visit_type_id_419:integer] │ Estimates: {rows: 2977093 (42.59MB), cpu: 42.59M, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [42]] Layout: [context_id_381:integer, created_by_id_383:integer, visit_type_id_419:integer] Fragment 40 [SOURCE] Output layout: [buy_lead_id_361, cta_slug_364, marketing_attribution_id_366] Output partitioning: HASH [buy_lead_id_361] ScanFilter[table = iceberg:mongo_marketing_attribution.buy_lead_cta_logs$data@6164463033804556162, dynamicFilters = {buy_lead_id_361 = #df_17298}] Layout: [buy_lead_id_361:integer, cta_slug_364:varchar, marketing_attribution_id_366:integer] Estimates: {rows: 28811712 (445.49MB), cpu: 445.49M, memory: 0B, network: 0B}/{rows: 28811712 (445.49MB), cpu: 445.49M, memory: 0B, network: 0B} cta_slug_364 := 5:cta_slug:varchar marketing_attribution_id_366 := 7:marketing_attribution_id:integer buy_lead_id_361 := 2:buy_lead_id:integer Fragment 41 [SOURCE] Output layout: [category_324, id_335] Output partitioning: HASH [id_335] TableScan[table = iceberg:sp_web.buy_lead_buylead$data@1299828741364571249] Layout: [category_324:varchar, id_335:integer] Estimates: {rows: 12700031 (127.01MB), cpu: 127.01M, memory: 0B, network: 0B} category_324 := 8:category:varchar id_335 := 19:id:integer Fragment 42 [SOURCE] Output layout: [context_id_381, created_by_id_383, visit_type_id_419] Output partitioning: HASH [context_id_381] TableScan[table = iceberg:sp_web.visits_visit$data@918499440402197125] Layout: [context_id_381:integer, created_by_id_383:integer, visit_type_id_419:integer] Estimates: {rows: 2977093 (42.59MB), cpu: 42.59M, memory: 0B, network: 0B} context_id_381 := 12:context_id:integer visit_type_id_419 := 50:visit_type_id:integer created_by_id_383 := 14:created_by_id:integer Fragment 43 [SOURCE] Output layout: [id_428, is_staff_432] Output partitioning: HASH [id_428] TableScan[table = iceberg:sp_web.spinny_auth_user$data@140806201974491105] Layout: [id_428:integer, is_staff_432:integer] Estimates: {rows: 17988382 (171.55MB), cpu: 171.55M, memory: 0B, network: 0B} id_428 := 7:id:integer is_staff_432 := 11:is_staff:integer Fragment 44 [SOURCE] Output layout: [id_450, utm_medium, utm_source, utm_term] Output partitioning: HASH [id_450] TableScan[table = iceberg:sp_web.marketing_marketingattribution$data@5810179578041371111] Layout: [id_450:integer, utm_medium:varchar, utm_source:varchar, utm_term:varchar] Estimates: {rows: 196944231 (5.05GB), cpu: 5.05G, memory: 0B, network: 0B} utm_term := 24:utm_term:varchar id_450 := 11:id:integer utm_medium := 22:utm_medium:varchar utm_source := 23:utm_source:varchar Fragment 45 [SOURCE] Output layout: [marketing_attribution_id_459, user_activity_type] Output partitioning: HASH [marketing_attribution_id_459] TableScan[table = iceberg:sp_cw_user_data_engine.user_activity_logger_useractivitylog$data@213815406515993458] Layout: [marketing_attribution_id_459:integer, user_activity_type:varchar] Estimates: {rows: 12125080 (117.48MB), cpu: 117.48M, memory: 0B, network: 0B} user_activity_type := 7:user_activity_type:varchar marketing_attribution_id_459 := 6:marketing_attribution_id:integer Fragment 46 [SOURCE] Output layout: [id_465] Output partitioning: BROADCAST [] TableScan[table = iceberg:sp_web.address_hub$data@7203458224615821150] Layout: [id_465:integer] Estimates: {rows: 141 (705B), cpu: 705, memory: 0B, network: 0B} id_465 := 24:id:integer Fragment 47 [SOURCE] Output layout: [display_name_472, id_473] Output partitioning: BROADCAST [] TableScan[table = iceberg:sp_web.address_city$data@3145091731273200997] Layout: [display_name_472:varchar, id_473:integer] Estimates: {rows: 454 (15.32kB), cpu: 15.32k, memory: 0B, network: 0B} id_473 := 5:id:integer display_name_472 := 3:display_name:varchar Fragment 48 [SOURCE] Output layout: [sell_lead_id_484, visit_id] Output partitioning: BROADCAST [] TableScan[table = iceberg:sp_web.buy_lead_testdrive$data@329118448009893483] Layout: [sell_lead_id_484:integer, visit_id:integer] Estimates: {rows: 3116766 (29.72MB), cpu: 29.72M, memory: 0B, network: 0B} visit_id := 20:visit_id:integer sell_lead_id_484 := 17:sell_lead_id:integer Fragment 49 [SOURCE] Output layout: [id_496, profile_id, tag_status] Output partitioning: HASH [id_496] TableScan[table = iceberg:sp_web.listing_lead$data@654511650163888914] Layout: [id_496:integer, profile_id:integer, tag_status:varchar] Estimates: {rows: 14393538 (210.65MB), cpu: 210.65M, memory: 0B, network: 0B} profile_id := 55:profile_id:integer tag_status := 70:tag_status:varchar id_496 := 26:id:integer Fragment 50 [SOURCE] Output layout: [id_514, registration_no] Output partitioning: HASH [id_514] TableScan[table = iceberg:sp_web.listing_leadprofile$data@3752956674780667051] Layout: [id_514:integer, registration_no:varchar] Estimates: {rows: 26793658 (513.68MB), cpu: 513.68M, memory: 0B, network: 0B} registration_no := 77:registration_no:varchar id_514 := 21:id:integer Fragment 51 [SOURCE] Output layout: [id_525] Output partitioning: BROADCAST [] ScanFilterProject[table = iceberg:sp_web.status_status$data@4176504356023197209, filterPredicate = (NOT $like(description_524, LikePattern '[%Cancel%]'))] Layout: [id_525:integer] Estimates: {rows: 604 (2.95kB), cpu: 29.74k, memory: 0B, network: 0B}/{rows: ? (?), cpu: 29.74k, memory: 0B, network: 0B}/{rows: ? (?), cpu: ?, memory: 0B, network: 0B} description_524 := 3:description:varchar id_525 := 5:id:integer Fragment 52 [HASH] Output layout: [id_611, expr_1303, expr_1305] Output partitioning: HASH [expr_1305] Project[] │ Layout: [id_611:integer, expr_1303:varchar(14), expr_1305:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ expr_1305 := CAST(id_611 AS varchar) └─ Project[] │ Layout: [id_611:integer, expr_1303:varchar(14)] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ Aggregate[keys = [id_611, expr_1303, expr_1279, expr_1284]] │ Layout: [id_611:integer, expr_1303:varchar(14), expr_1279:varchar, expr_1284:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} └─ Project[] │ Layout: [id_611:integer, expr_1284:varchar, expr_1279:varchar, expr_1303:varchar(14)] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ expr_1303 := (CASE WHEN (expr_1302 = varchar '591918414') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar '{offer_ref_id}') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar '3dot14') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'acemediaplus_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'adapptmobi') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'adcanopus') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'adcanopus_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'adcountryindia') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'adcountymedia_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'adpiece_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'adsvmedia_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'affinityveve') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'affleagency') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'amazus_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'appfloodaff_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'appitate_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'applabs_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'applabsmedia') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'appmontize') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'Appmontize1') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'appnext_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'atmoicads_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'backgardon_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'betop_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'blueocean_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'cheeringads_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'cooins_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'CRM') THEN varchar(14) 'App_CRM' WHEN (expr_1302 = varchar 'dech_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'dehheit_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'digitalverse_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'erinlabs') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'Facebook Ads') THEN varchar(14) 'App_Facebook' WHEN (expr_1302 = varchar 'gads_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'glance_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'googleadwords_int') THEN varchar(14) 'App_Google' WHEN (expr_1302 = varchar 'gourdmobiads_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'hasoffers_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'Hotstar') THEN varchar(14) 'App_Hotstar' WHEN (expr_1302 = varchar 'Hotstar') THEN varchar(14) 'App_Hotstar' WHEN (expr_1302 = varchar 'icolorfast_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'icubeswire') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'inmobi_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'inmobiagency') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'intellect_ads') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'intellectads') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'jumboads') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'kickcash_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'linmobi_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'livetopmedia_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'madcube_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'maopumedia_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'marlinads_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'mediaversedigis') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'mediaxpediatech') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'mobavenue') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'mobfountain2') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'mobpine_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'mobuppagency') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'mobupps_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'mobuppsagency') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'mobwide_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'mocaglobal') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'multiads_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'oneenginemedia') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'Organic') THEN varchar(14) 'App_Organic' WHEN (expr_1302 = varchar 'orilmobi_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'plusgamesgo_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'poche_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'pokktmkt') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'pokktperformance_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'prodigital') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'profuseservices_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'QR_code') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'QR_code') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'restricted') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'restricted') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'royomobi_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'seikoads_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'sharechat_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'siftco_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'simplyverses_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'Spinny') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'Spinny_Affle_PanIndia') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'Spinny_Android') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'Spotify') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'starrytech_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'surfertech_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'taboola_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'Tarsan') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'tempoads_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'test') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'test_fb_ak') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'tjzymob_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'TVF_Youtube') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'upsflyer_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'vcommission') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'verseiume_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'vestaapps_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'vidmobads_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'vserv') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'WhatsApp') THEN varchar(14) 'App_Whatsapp' WHEN (expr_1302 = varchar 'xyadsagency') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'axismobi') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'adzealous') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'econnectmobi') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'applabsmedia') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'magixengage') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'Auto-Car-Video') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'fillymedia') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'quickadsmedia') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'inmobidsp_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'blendaidigital') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'Apple Search Ads') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'ballyhoomedia') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'nativemonetize') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'Appnext') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'Email') THEN varchar(14) 'App_CRM' WHEN (expr_1302 = varchar 'Social_instagram') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'mobavenue_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'Survey') THEN varchar(14) 'App_CRM' WHEN (expr_1302 = varchar 'lucrative') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'aimarkit') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'flickstree') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'GlobalWideMedia') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'geoadmedia_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'globalwide_int') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'mobisaturntechn') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'mrndigital') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'unilead_network') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'optimidea') THEN varchar(14) 'App_Affiliates' WHEN (expr_1302 = varchar 'zorkanetwork') THEN varchar(14) 'App_Affiliates' ELSE varchar(14) 'App_organic' END) └─ Project[] │ Layout: [id_611:integer, expr_1302:varchar, expr_1284:varchar, expr_1279:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ Aggregate[type = FINAL, keys = [id_611, expr_1300, expr_1301, expr_1282, expr_1281, display_name_1287, expr_1280, expr_1302, expr_1283, expr_1284, expr_1279]] │ Layout: [id_611:integer, expr_1300:varchar(6), expr_1301:varchar(2), expr_1282:varchar, expr_1281:varchar, display_name_1287:varchar, expr_1280:varchar, expr_1302:varchar, expr_1283:date, expr_1284:varchar, expr_1279:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} └─ LocalExchange[partitioning = HASH, arguments = [id_611::integer, expr_1284::varchar, expr_1279::varchar]] │ Layout: [id_611:integer, expr_1300:varchar(6), expr_1301:varchar(2), expr_1282:varchar, expr_1281:varchar, display_name_1287:varchar, expr_1280:varchar, expr_1302:varchar, expr_1283:date, expr_1284:varchar, expr_1279:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ Aggregate[type = PARTIAL, keys = [id_611, expr_1300, expr_1301, expr_1282, expr_1281, display_name_1287, expr_1280, expr_1302, expr_1283, expr_1284, expr_1279]] │ Layout: [id_611:integer, expr_1300:varchar(6), expr_1301:varchar(2), expr_1282:varchar, expr_1281:varchar, display_name_1287:varchar, expr_1280:varchar, expr_1302:varchar, expr_1283:date, expr_1284:varchar, expr_1279:varchar] └─ Project[] │ Layout: [id_611:integer, expr_1279:varchar, expr_1280:varchar, expr_1281:varchar, expr_1282:varchar, expr_1283:date, expr_1284:varchar, display_name_1287:varchar, expr_1300:varchar(6), expr_1301:varchar(2), expr_1302:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ expr_1300 := (CASE WHEN $like(platform_source_620, LikePattern '[%app_%]') THEN varchar(6) 'App' WHEN $like(platform_source_620, LikePattern '[%web%]') THEN varchar(6) 'Web' WHEN $like(platform_source_620, LikePattern '[%mweb_%]') THEN varchar(6) 'Web' ELSE varchar(6) 'Others' END) │ expr_1301 := (CASE WHEN $like(expr_1279, LikePattern '[%RM%]') THEN varchar(2) 'RM' WHEN $like(expr_1279, LikePattern '[%PR%]') THEN varchar(2) 'PR' ELSE null::varchar(2) END) │ expr_1302 := (CASE WHEN (expr_1281 = varchar '') THEN expr_1280 ELSE expr_1281 END) └─ LeftJoin[criteria = (city_id_601 = id_1289), distribution = REPLICATED] │ Layout: [id_611:integer, platform_source_620:varchar, expr_1279:varchar, expr_1280:varchar, expr_1281:varchar, expr_1282:varchar, expr_1283:date, expr_1284:varchar, display_name_1287:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 91.90kB, network: 0B} │ Distribution: REPLICATED │ maySkipOutputDuplicates = true ├─ LeftJoin[criteria = (id_611 = expr_1277), distribution = PARTITIONED] │ │ Layout: [city_id_601:integer, platform_source_620:varchar, id_611:integer, expr_1279:varchar, expr_1280:varchar, expr_1281:varchar, expr_1282:varchar, expr_1283:date, expr_1284:varchar] │ │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} │ │ Distribution: PARTITIONED │ │ maySkipOutputDuplicates = true │ ├─ InnerJoin[criteria = (id_611 = context_id_552), filter = (CAST($operator$add(created_on_555, interval day to second '0 05:30:00.000') AS date) >= date '2024-03-12'), distribution = PARTITIONED] │ │ │ Layout: [city_id_601:integer, id_611:integer, platform_source_620:varchar] │ │ │ Estimates: {rows: ? (?), cpu: ?, memory: 51.10MB, network: 0B} │ │ │ Distribution: PARTITIONED │ │ │ maySkipOutputDuplicates = true │ │ │ dynamicFilterAssignments = {context_id_552 -> #df_17332} │ │ ├─ RemoteSource[sourceFragmentIds = [53]] │ │ │ Layout: [city_id_601:integer, id_611:integer, platform_source_620:varchar] │ │ └─ LocalExchange[partitioning = HASH, arguments = [context_id_552::integer]] │ │ │ Layout: [context_id_552:integer, created_on_555:timestamp(6) with time zone] │ │ │ Estimates: {rows: 2977093 (51.10MB), cpu: 51.10M, memory: 0B, network: 0B} │ │ └─ RemoteSource[sourceFragmentIds = [54]] │ │ Layout: [context_id_552:integer, created_on_555:timestamp(6) with time zone] │ └─ LocalExchange[partitioning = HASH, arguments = [expr_1277::integer]] │ │ Layout: [expr_1277:integer, expr_1279:varchar, expr_1280:varchar, expr_1281:varchar, expr_1282:varchar, expr_1283:date, expr_1284:varchar] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ └─ RemoteSource[sourceFragmentIds = [55]] │ Layout: [expr_1277:integer, expr_1279:varchar, expr_1280:varchar, expr_1281:varchar, expr_1282:varchar, expr_1283:date, expr_1284:varchar] └─ LocalExchange[partitioning = SINGLE] │ Layout: [display_name_1287:varchar, id_1289:integer] │ Estimates: {rows: 454 (15.32kB), cpu: 0, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [74]] Layout: [display_name_1287:varchar, id_1289:integer] Fragment 53 [SOURCE] Output layout: [city_id_601, id_611, platform_source_620] Output partitioning: HASH [id_611] ScanFilterProject[table = iceberg:sp_web.buy_lead_buylead$data@1299828741364571249, filterPredicate = ((category_600 = varchar 'assured') AND $like(platform_source_620, LikePattern '[%app%]')), dynamicFilters = {id_611 = #df_17332}] Layout: [city_id_601:integer, id_611:integer, platform_source_620:varchar] Estimates: {rows: 12700031 (191.60MB), cpu: 258.05M, memory: 0B, network: 0B}/{rows: 5715014 (86.22MB), cpu: 258.05M, memory: 0B, network: 0B}/{rows: 5715014 (86.22MB), cpu: 86.22M, memory: 0B, network: 0B} city_id_601 := 9:city_id:integer category_600 := 8:category:varchar platform_source_620 := 28:platform_source:varchar id_611 := 19:id:integer Fragment 54 [SOURCE] Output layout: [context_id_552, created_on_555] Output partitioning: HASH [context_id_552] TableScan[table = iceberg:sp_web.visits_visit$data@918499440402197125] Layout: [context_id_552:integer, created_on_555:timestamp(6) with time zone] Estimates: {rows: 2977093 (51.10MB), cpu: 51.10M, memory: 0B, network: 0B} context_id_552 := 12:context_id:integer created_on_555 := 15:created_on:timestamp(6) with time zone Fragment 55 [HASH] Output layout: [expr_1277, expr_1279, expr_1280, expr_1281, expr_1282, expr_1283, expr_1284] Output partitioning: HASH [expr_1277] Project[] │ Layout: [expr_1277:integer, expr_1279:varchar, expr_1280:varchar, expr_1281:varchar, expr_1282:varchar, expr_1283:date, expr_1284:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ expr_1277 := COALESCE(id_966, id_706) │ expr_1279 := COALESCE(campaign_1158, campaign_779) │ expr_1280 := COALESCE(media_source_1227, media_source_848) │ expr_1281 := COALESCE(partner_1235, partner_856) │ expr_1282 := COALESCE(platform_1237, platform_858) │ expr_1283 := COALESCE(expr_1267, expr_888) │ expr_1284 := COALESCE(adset_1139, adset_760) └─ FullJoin[criteria = (id_706 = id_966), distribution = PARTITIONED] │ Layout: [id_706:integer, campaign_779:varchar, media_source_848:varchar, partner_856:varchar, platform_858:varchar, expr_888:date, adset_760:varchar, id_966:integer, campaign_1158:varchar, media_source_1227:varchar, partner_1235:varchar, platform_1237:varchar, expr_1267:date, adset_1139:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} │ Distribution: PARTITIONED │ maySkipOutputDuplicates = true ├─ FilterProject[filterPredicate = (row_number_894 = bigint '1')] │ │ Layout: [id_706:integer, campaign_779:varchar, media_source_848:varchar, partner_856:varchar, platform_858:varchar, expr_888:date, adset_760:varchar] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B}/{rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ └─ Project[] │ │ Layout: [id_706:integer, campaign_779:varchar, media_source_848:varchar, partner_856:varchar, platform_858:varchar, expr_888:date, adset_760:varchar, row_number_894:bigint] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ └─ TopNRanking[partitionBy = [id_706], orderBy = [event_time_823 DESC NULLS LAST], limit = 1] │ │ Layout: [id_706:integer, campaign_779:varchar, event_time_823:varchar, media_source_848:varchar, partner_856:varchar, platform_858:varchar, expr_888:date, adset_760:varchar, row_number_894:bigint] │ │ row_number_894 := ROW_NUMBER │ └─ Project[] │ │ Layout: [id_706:integer, campaign_779:varchar, event_time_823:varchar, media_source_848:varchar, partner_856:varchar, platform_858:varchar, expr_888:date, adset_760:varchar] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ └─ TopNRanking[partitionBy = [id_706], orderBy = [event_time_823 DESC NULLS LAST], limit = 1] │ │ Layout: [id_706:integer, campaign_779:varchar, event_time_823:varchar, media_source_848:varchar, partner_856:varchar, platform_858:varchar, expr_888:date, adset_760:varchar, row_number_893:bigint] │ │ row_number_893 := ROW_NUMBER │ └─ FilterProject[filterPredicate = (dense_rank_892 = bigint '1')] │ │ Layout: [id_706:integer, campaign_779:varchar, event_time_823:varchar, media_source_848:varchar, partner_856:varchar, platform_858:varchar, expr_888:date, adset_760:varchar] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B}/{rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ └─ Project[] │ │ Layout: [id_706:integer, campaign_779:varchar, event_time_823:varchar, media_source_848:varchar, partner_856:varchar, platform_858:varchar, expr_888:date, adset_760:varchar, dense_rank_892:bigint] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ └─ Window[partitionBy = [], orderBy = [expr_891 DESC NULLS LAST]] │ │ Layout: [id_706:integer, campaign_779:varchar, event_time_823:varchar, media_source_848:varchar, partner_856:varchar, platform_858:varchar, expr_888:date, adset_760:varchar, expr_891:integer, dense_rank_892:bigint] │ │ dense_rank_892 := dense_rank() RANGE UNBOUNDED_PRECEDING CURRENT_ROW │ └─ FilterProject[filterPredicate = (dense_rank = bigint '1')] │ │ Layout: [id_706:integer, campaign_779:varchar, event_time_823:varchar, media_source_848:varchar, partner_856:varchar, platform_858:varchar, expr_888:date, adset_760:varchar, expr_891:integer] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B}/{rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ │ expr_891 := $operator$add($operator$add(max, max_889), max_890) │ └─ Window[partitionBy = [id_706], orderBy = [max DESC NULLS LAST]] │ │ Layout: [id_706:integer, campaign_779:varchar, event_time_823:varchar, media_source_848:varchar, partner_856:varchar, platform_858:varchar, expr_888:date, adset_760:varchar, max:integer, max_889:integer, max_890:integer, dense_rank:bigint] │ │ dense_rank := dense_rank() RANGE UNBOUNDED_PRECEDING CURRENT_ROW │ └─ Project[] │ │ Layout: [id_706:integer, campaign_779:varchar, event_time_823:varchar, media_source_848:varchar, partner_856:varchar, platform_858:varchar, expr_888:date, adset_760:varchar, max:integer, max_889:integer, max_890:integer] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ └─ Aggregate[keys = [id_706, expr_754, event_name_818, campaign_779, event_time_823, expr_884, media_source_848, partner_856, platform_858, expr_888, adset_760]] │ │ Layout: [id_706:integer, expr_754:date, event_name_818:varchar, campaign_779:varchar, event_time_823:varchar, expr_884:timestamp(3), media_source_848:varchar, partner_856:varchar, platform_858:varchar, expr_888:date, adset_760:varchar, max:integer, max_889:integer, max_890:integer] │ │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} │ │ max := max(expr_885) │ │ max_889 := max(expr_886) │ │ max_890 := max(expr_887) │ └─ Project[] │ │ Layout: [id_706:integer, expr_754:date, event_name_818:varchar, campaign_779:varchar, media_source_848:varchar, platform_858:varchar, partner_856:varchar, adset_760:varchar, expr_884:timestamp(3), event_time_823:varchar, expr_885:integer, expr_886:integer, expr_887:integer, expr_888:date] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ └─ Aggregate[keys = [id_706, expr_754, event_name_818, campaign_779, media_source_848, platform_858, partner_856, is_primary_attribution_840, is_retargeting_842, adset_760, expr_884, event_time_823, row_number_883, expr_885, expr_886, expr_887, expr_888]] │ │ Layout: [id_706:integer, expr_754:date, event_name_818:varchar, campaign_779:varchar, media_source_848:varchar, platform_858:varchar, partner_856:varchar, is_primary_attribution_840:varchar, is_retargeting_842:varchar, adset_760:varchar, expr_884:timestamp(3), event_time_823:varchar, row_number_883:bigint, expr_885:integer, expr_886:integer, expr_887:integer, expr_888:date] │ │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} │ └─ Project[] │ │ Layout: [id_706:integer, expr_754:date, adset_760:varchar, campaign_779:varchar, event_name_818:varchar, event_time_823:varchar, is_primary_attribution_840:varchar, is_retargeting_842:varchar, media_source_848:varchar, partner_856:varchar, platform_858:varchar, row_number_883:bigint, expr_884:timestamp(3), expr_885:integer, expr_886:integer, expr_887:integer, expr_888:date] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ │ expr_884 := (CASE WHEN (length(trim(event_time_823)) = bigint '0') THEN null::timestamp(3) WHEN $like(event_time_823, LikePattern '[%T%]') THEN date_parse(event_time_823, varchar(18) '%Y-%m-%dT%H:%i:%sZ') ELSE date_parse(event_time_823, varchar(17) '%Y-%m-%d %H:%i:%s') END) │ │ expr_885 := (CASE WHEN (event_name_818 = varchar 'af_demand_q3') THEN integer '3' WHEN (event_name_818 = varchar 'af_demand_q2') THEN integer '2' WHEN (event_name_818 = varchar 'af_demand_q1') THEN integer '1' ELSE integer '0' END) │ │ expr_886 := (CASE WHEN (is_primary_attribution_840 = varchar 'true') THEN integer '1' ELSE integer '0' END) │ │ expr_887 := (CASE WHEN (is_retargeting_842 = varchar 'true') THEN integer '1' ELSE integer '0' END) │ │ expr_888 := CAST($operator$add((CASE WHEN (length(trim(install_time_837)) = bigint '0') THEN null::timestamp(3) WHEN $like(install_time_837, LikePattern '[%T%]') THEN date_parse(install_time_837, varchar(18) '%Y-%m-%dT%H:%i:%sZ') ELSE date_parse(install_time_837, varchar(17) '%Y-%m-%d %H:%i:%s') END), interval day to second '0 05:30:00.000') AS date) │ └─ Window[partitionBy = [id_706], orderBy = [event_time_823 DESC NULLS LAST]] │ │ Layout: [id_706:integer, expr_754:date, adset_760:varchar, campaign_779:varchar, event_name_818:varchar, event_time_823:varchar, install_time_837:varchar, is_primary_attribution_840:varchar, is_retargeting_842:varchar, media_source_848:varchar, partner_856:varchar, platform_858:varchar, row_number_883:bigint] │ │ row_number_883 := row_number() RANGE UNBOUNDED_PRECEDING CURRENT_ROW │ └─ LocalExchange[partitioning = HASH, arguments = [id_706::integer]] │ │ Layout: [id_706:integer, expr_754:date, adset_760:varchar, campaign_779:varchar, event_name_818:varchar, event_time_823:varchar, install_time_837:varchar, is_primary_attribution_840:varchar, is_retargeting_842:varchar, media_source_848:varchar, partner_856:varchar, platform_858:varchar] │ │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ └─ RemoteSource[sourceFragmentIds = [56]] │ Layout: [id_706:integer, expr_754:date, adset_760:varchar, campaign_779:varchar, event_name_818:varchar, event_time_823:varchar, install_time_837:varchar, is_primary_attribution_840:varchar, is_retargeting_842:varchar, media_source_848:varchar, partner_856:varchar, platform_858:varchar] └─ FilterProject[filterPredicate = (row_number_1275 = bigint '1')] │ Layout: [id_966:integer, campaign_1158:varchar, media_source_1227:varchar, partner_1235:varchar, platform_1237:varchar, expr_1267:date, adset_1139:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B}/{rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ Project[] │ Layout: [id_966:integer, campaign_1158:varchar, media_source_1227:varchar, partner_1235:varchar, platform_1237:varchar, expr_1267:date, adset_1139:varchar, row_number_1275:bigint] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ TopNRanking[partitionBy = [id_966], orderBy = [event_time_1202 DESC NULLS LAST], limit = 1] │ Layout: [id_966:integer, campaign_1158:varchar, event_time_1202:varchar, media_source_1227:varchar, partner_1235:varchar, platform_1237:varchar, expr_1267:date, adset_1139:varchar, row_number_1275:bigint] │ row_number_1275 := ROW_NUMBER └─ Project[] │ Layout: [id_966:integer, campaign_1158:varchar, event_time_1202:varchar, media_source_1227:varchar, partner_1235:varchar, platform_1237:varchar, expr_1267:date, adset_1139:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ TopNRanking[partitionBy = [id_966], orderBy = [event_time_1202 DESC NULLS LAST], limit = 1] │ Layout: [id_966:integer, campaign_1158:varchar, event_time_1202:varchar, media_source_1227:varchar, partner_1235:varchar, platform_1237:varchar, expr_1267:date, adset_1139:varchar, row_number_1274:bigint] │ row_number_1274 := ROW_NUMBER └─ FilterProject[filterPredicate = (dense_rank_1273 = bigint '1')] │ Layout: [id_966:integer, campaign_1158:varchar, event_time_1202:varchar, media_source_1227:varchar, partner_1235:varchar, platform_1237:varchar, expr_1267:date, adset_1139:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B}/{rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ Project[] │ Layout: [id_966:integer, campaign_1158:varchar, event_time_1202:varchar, media_source_1227:varchar, partner_1235:varchar, platform_1237:varchar, expr_1267:date, adset_1139:varchar, dense_rank_1273:bigint] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ Window[partitionBy = [], orderBy = [expr_1272 DESC NULLS LAST]] │ Layout: [id_966:integer, campaign_1158:varchar, event_time_1202:varchar, media_source_1227:varchar, partner_1235:varchar, platform_1237:varchar, expr_1267:date, adset_1139:varchar, expr_1272:integer, dense_rank_1273:bigint] │ dense_rank_1273 := dense_rank() RANGE UNBOUNDED_PRECEDING CURRENT_ROW └─ FilterProject[filterPredicate = (dense_rank_1271 = bigint '1')] │ Layout: [id_966:integer, campaign_1158:varchar, event_time_1202:varchar, media_source_1227:varchar, partner_1235:varchar, platform_1237:varchar, expr_1267:date, adset_1139:varchar, expr_1272:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B}/{rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ expr_1272 := $operator$add($operator$add(max_1268, max_1269), max_1270) └─ Window[partitionBy = [id_966], orderBy = [max_1268 DESC NULLS LAST]] │ Layout: [id_966:integer, campaign_1158:varchar, event_time_1202:varchar, media_source_1227:varchar, partner_1235:varchar, platform_1237:varchar, expr_1267:date, adset_1139:varchar, max_1268:integer, max_1269:integer, max_1270:integer, dense_rank_1271:bigint] │ dense_rank_1271 := dense_rank() RANGE UNBOUNDED_PRECEDING CURRENT_ROW └─ Project[] │ Layout: [id_966:integer, campaign_1158:varchar, event_time_1202:varchar, media_source_1227:varchar, partner_1235:varchar, platform_1237:varchar, expr_1267:date, adset_1139:varchar, max_1268:integer, max_1269:integer, max_1270:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ Aggregate[keys = [id_966, expr_1133, event_name_1197, campaign_1158, event_time_1202, expr_1263, media_source_1227, partner_1235, platform_1237, expr_1267, adset_1139]] │ Layout: [id_966:integer, expr_1133:date, event_name_1197:varchar, campaign_1158:varchar, event_time_1202:varchar, expr_1263:timestamp(3), media_source_1227:varchar, partner_1235:varchar, platform_1237:varchar, expr_1267:date, adset_1139:varchar, max_1268:integer, max_1269:integer, max_1270:integer] │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} │ max_1268 := max(expr_1264) │ max_1269 := max(expr_1265) │ max_1270 := max(expr_1266) └─ Project[] │ Layout: [id_966:integer, expr_1133:date, event_name_1197:varchar, campaign_1158:varchar, media_source_1227:varchar, platform_1237:varchar, partner_1235:varchar, adset_1139:varchar, expr_1263:timestamp(3), event_time_1202:varchar, expr_1264:integer, expr_1265:integer, expr_1266:integer, expr_1267:date] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ Aggregate[keys = [id_966, expr_1133, event_name_1197, campaign_1158, media_source_1227, platform_1237, partner_1235, is_primary_attribution_1219, is_retargeting_1221, adset_1139, expr_1263, event_time_1202, row_number_1262, expr_1264, expr_1265, expr_1266, expr_1267]] │ Layout: [id_966:integer, expr_1133:date, event_name_1197:varchar, campaign_1158:varchar, media_source_1227:varchar, platform_1237:varchar, partner_1235:varchar, is_primary_attribution_1219:varchar, is_retargeting_1221:varchar, adset_1139:varchar, expr_1263:timestamp(3), event_time_1202:varchar, row_number_1262:bigint, expr_1264:integer, expr_1265:integer, expr_1266:integer, expr_1267:date] │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} └─ FilterProject[filterPredicate = (event_name_1197 = varchar 'af_demand_q3')] │ Layout: [id_966:integer, expr_1133:date, adset_1139:varchar, campaign_1158:varchar, event_name_1197:varchar, event_time_1202:varchar, is_primary_attribution_1219:varchar, is_retargeting_1221:varchar, media_source_1227:varchar, partner_1235:varchar, platform_1237:varchar, row_number_1262:bigint, expr_1263:timestamp(3), expr_1264:integer, expr_1265:integer, expr_1266:integer, expr_1267:date] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B}/{rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ expr_1263 := (CASE WHEN (length(trim(event_time_1202)) = bigint '0') THEN null::timestamp(3) WHEN $like(event_time_1202, LikePattern '[%T%]') THEN date_parse(event_time_1202, varchar(18) '%Y-%m-%dT%H:%i:%sZ') ELSE date_parse(event_time_1202, varchar(17) '%Y-%m-%d %H:%i:%s') END) │ expr_1264 := (CASE WHEN (event_name_1197 = varchar 'af_demand_q3') THEN integer '3' WHEN (event_name_1197 = varchar 'af_demand_q2') THEN integer '2' WHEN (event_name_1197 = varchar 'af_demand_q1') THEN integer '1' ELSE integer '0' END) │ expr_1265 := (CASE WHEN (is_primary_attribution_1219 = varchar 'true') THEN integer '1' ELSE integer '0' END) │ expr_1266 := (CASE WHEN (is_retargeting_1221 = varchar 'true') THEN integer '1' ELSE integer '0' END) │ expr_1267 := CAST($operator$add((CASE WHEN (length(trim(install_time_1216)) = bigint '0') THEN null::timestamp(3) WHEN $like(install_time_1216, LikePattern '[%T%]') THEN date_parse(install_time_1216, varchar(18) '%Y-%m-%dT%H:%i:%sZ') ELSE date_parse(install_time_1216, varchar(17) '%Y-%m-%d %H:%i:%s') END), interval day to second '0 05:30:00.000') AS date) └─ Window[partitionBy = [id_966], orderBy = [event_time_1202 DESC NULLS LAST]] │ Layout: [id_966:integer, expr_1133:date, adset_1139:varchar, campaign_1158:varchar, event_name_1197:varchar, event_time_1202:varchar, install_time_1216:varchar, is_primary_attribution_1219:varchar, is_retargeting_1221:varchar, media_source_1227:varchar, partner_1235:varchar, platform_1237:varchar, row_number_1262:bigint] │ row_number_1262 := row_number() RANGE UNBOUNDED_PRECEDING CURRENT_ROW └─ LocalExchange[partitioning = HASH, arguments = [id_966::integer]] │ Layout: [id_966:integer, expr_1133:date, adset_1139:varchar, campaign_1158:varchar, event_name_1197:varchar, event_time_1202:varchar, install_time_1216:varchar, is_primary_attribution_1219:varchar, is_retargeting_1221:varchar, media_source_1227:varchar, partner_1235:varchar, platform_1237:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [65]] Layout: [id_966:integer, expr_1133:date, adset_1139:varchar, campaign_1158:varchar, event_name_1197:varchar, event_time_1202:varchar, install_time_1216:varchar, is_primary_attribution_1219:varchar, is_retargeting_1221:varchar, media_source_1227:varchar, partner_1235:varchar, platform_1237:varchar] Fragment 56 [HASH] Output layout: [id_706, expr_754, adset_760, campaign_779, event_name_818, event_time_823, install_time_837, is_primary_attribution_840, is_retargeting_842, media_source_848, partner_856, platform_858] Output partitioning: HASH [id_706] InnerJoin[criteria = (device_id = customer_user_id_810), filter = ((CAST(sp_created_at_868 AS date) >= date '2024-03-12') AND (expr_1310 <= CAST($operator$add(created_on_650, interval day to second '0 05:30:00.000') AS date))), distribution = PARTITIONED] │ Layout: [id_706:integer, expr_754:date, adset_760:varchar, campaign_779:varchar, event_name_818:varchar, event_time_823:varchar, install_time_837:varchar, is_primary_attribution_840:varchar, is_retargeting_842:varchar, media_source_848:varchar, partner_856:varchar, platform_858:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 166.27GB, network: 0B} │ Distribution: PARTITIONED ├─ RemoteSource[sourceFragmentIds = [57]] │ Layout: [id_706:integer, device_id:varchar, created_on_650:timestamp(6) with time zone, expr_754:date] └─ LocalExchange[partitioning = HASH, arguments = [customer_user_id_810::varchar]] │ Layout: [adset_760:varchar, campaign_779:varchar, customer_user_id_810:varchar, event_name_818:varchar, event_time_823:varchar, install_time_837:varchar, is_primary_attribution_840:varchar, is_retargeting_842:varchar, media_source_848:varchar, partner_856:varchar, platform_858:varchar, sp_created_at_868:timestamp(6) with time zone, expr_1310:date] │ Estimates: {rows: 338914598 (166.27GB), cpu: 166.27G, memory: 0B, network: 0B} └─ Project[] │ Layout: [adset_760:varchar, campaign_779:varchar, customer_user_id_810:varchar, event_name_818:varchar, event_time_823:varchar, install_time_837:varchar, is_primary_attribution_840:varchar, is_retargeting_842:varchar, media_source_848:varchar, partner_856:varchar, platform_858:varchar, sp_created_at_868:timestamp(6) with time zone, expr_1310:date] │ Estimates: {rows: 338914598 (166.27GB), cpu: 166.27G, memory: 0B, network: 0B} │ expr_1310 := CAST($operator$add((CASE WHEN (length(trim(event_time_823)) = bigint '0') THEN null::timestamp(3) WHEN $like(event_time_823, LikePattern '[%T%]') THEN date_parse(event_time_823, varchar(18) '%Y-%m-%dT%H:%i:%sZ') ELSE date_parse(event_time_823, varchar(17) '%Y-%m-%d %H:%i:%s') END), interval day to second '0 05:30:00.000') AS date) └─ RemoteSource[sourceFragmentIds = [64]] Layout: [adset_760:varchar, campaign_779:varchar, customer_user_id_810:varchar, event_name_818:varchar, event_time_823:varchar, install_time_837:varchar, is_primary_attribution_840:varchar, is_retargeting_842:varchar, media_source_848:varchar, partner_856:varchar, platform_858:varchar, sp_created_at_868:timestamp(6) with time zone] Fragment 57 [HASH] Output layout: [id_706, device_id, created_on_650, expr_754] Output partitioning: HASH [device_id] Project[] │ Layout: [id_706:integer, device_id:varchar, created_on_650:timestamp(6) with time zone, expr_754:date] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ Aggregate[keys = [id_706, device_id, row_number_753, created_on_650, expr_754]] │ Layout: [id_706:integer, device_id:varchar, row_number_753:bigint, created_on_650:timestamp(6) with time zone, expr_754:date] │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} └─ FilterProject[filterPredicate = (row_number_753 = bigint '1')] │ Layout: [created_on_650:timestamp(6) with time zone, id_706:integer, device_id:varchar, row_number_753:bigint, expr_754:date] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B}/{rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ expr_754 := CAST($operator$add(created_on_699, interval day to second '0 05:30:00.000') AS date) └─ Project[] │ Layout: [created_on_650:timestamp(6) with time zone, created_on_699:timestamp(6) with time zone, id_706:integer, device_id:varchar, row_number_753:bigint] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ TopNRanking[partitionBy = [id_706], orderBy = [event_time DESC NULLS LAST], limit = 1] │ Layout: [created_on_650:timestamp(6) with time zone, created_on_699:timestamp(6) with time zone, id_706:integer, device_id:varchar, event_time:varchar, row_number_753:bigint] │ row_number_753 := ROW_NUMBER └─ LocalExchange[partitioning = HASH, arguments = [id_706::integer]] │ Layout: [created_on_650:timestamp(6) with time zone, created_on_699:timestamp(6) with time zone, id_706:integer, device_id:varchar, event_time:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [58]] Layout: [created_on_650:timestamp(6) with time zone, created_on_699:timestamp(6) with time zone, id_706:integer, device_id:varchar, event_time:varchar] Fragment 58 [HASH] Output layout: [created_on_650, created_on_699, id_706, device_id, event_time] Output partitioning: HASH [id_706] TopNRanking[partitionBy = [id_706], orderBy = [event_time DESC NULLS LAST], limit = 1] │ Layout: [created_on_650:timestamp(6) with time zone, id_706:integer, created_on_699:timestamp(6) with time zone, device_id:varchar, event_time:varchar] │ row_number_753 := ROW_NUMBER └─ InnerJoin[criteria = (device_id = customer_user_id), filter = ((CAST($operator$add(created_on_650, interval day to second '0 05:30:00.000') AS date) >= date '2024-03-12') AND (CAST(sp_created_at AS date) >= date '2024-03-12') AND (expr_1311 <= CAST($operator$add(created_on_650, interval day to second '0 05:30:00.000') AS date))), distribution = PARTITIONED] │ Layout: [created_on_650:timestamp(6) with time zone, id_706:integer, created_on_699:timestamp(6) with time zone, device_id:varchar, event_time:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} │ Distribution: PARTITIONED │ dynamicFilterAssignments = {customer_user_id -> #df_17339} ├─ RemoteSource[sourceFragmentIds = [59]] │ Layout: [created_on_650:timestamp(6) with time zone, id_706:integer, created_on_699:timestamp(6) with time zone, device_id:varchar] └─ LocalExchange[partitioning = HASH, arguments = [customer_user_id::varchar]] │ Layout: [customer_user_id:varchar, event_time:varchar, sp_created_at:timestamp(6) with time zone, expr_1311:date] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ Project[] │ Layout: [customer_user_id:varchar, event_time:varchar, sp_created_at:timestamp(6) with time zone, expr_1311:date] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ expr_1311 := CAST($operator$add((CASE WHEN (length(trim(event_time)) = bigint '0') THEN null::timestamp(3) WHEN $like(event_time, LikePattern '[%T%]') THEN date_parse(event_time, varchar(18) '%Y-%m-%dT%H:%i:%sZ') ELSE date_parse(event_time, varchar(17) '%Y-%m-%d %H:%i:%s') END), interval day to second '0 05:30:00.000') AS date) └─ RemoteSource[sourceFragmentIds = [63]] Layout: [customer_user_id:varchar, event_time:varchar, sp_created_at:timestamp(6) with time zone] Fragment 59 [HASH] Output layout: [created_on_650, id_706, created_on_699, device_id] Output partitioning: HASH [device_id] InnerJoin[criteria = (account_id_688 = account_id_731), distribution = PARTITIONED] │ Layout: [created_on_699:timestamp(6) with time zone, id_706:integer, created_on_650:timestamp(6) with time zone, device_id:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 988.54MB, network: 0B} │ Distribution: PARTITIONED │ dynamicFilterAssignments = {account_id_731 -> #df_17341} ├─ RemoteSource[sourceFragmentIds = [60]] │ Layout: [account_id_688:integer, created_on_699:timestamp(6) with time zone, id_706:integer, created_on_650:timestamp(6) with time zone] └─ LocalExchange[partitioning = HASH, arguments = [account_id_731::integer]] │ Layout: [account_id_731:integer, device_id:varchar] │ Estimates: {rows: 7530135 (988.54MB), cpu: 988.54M, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [62]] Layout: [account_id_731:integer, device_id:varchar] Fragment 60 [SOURCE] Output layout: [account_id_688, created_on_699, id_706, created_on_650] Output partitioning: HASH [account_id_688] InnerJoin[criteria = (id_706 = context_id_647), distribution = REPLICATED] │ Layout: [account_id_688:integer, created_on_699:timestamp(6) with time zone, id_706:integer, created_on_650:timestamp(6) with time zone] │ Estimates: {rows: ? (?), cpu: ?, memory: 306.63MB, network: 0B} │ Distribution: REPLICATED │ dynamicFilterAssignments = {context_id_647 -> #df_17342} ├─ ScanFilterProject[table = iceberg:sp_web.buy_lead_buylead$data@1299828741364571249, filterPredicate = $like(platform_source_715, LikePattern '[%app%]'), dynamicFilters = {account_id_688 = #df_17341, id_706 = #df_17342}] │ Layout: [account_id_688:integer, created_on_699:timestamp(6) with time zone, id_706:integer] │ Estimates: {rows: 12700031 (278.56MB), cpu: 349.15M, memory: 0B, network: 0B}/{rows: 11430028 (250.70MB), cpu: 349.15M, memory: 0B, network: 0B}/{rows: 11430028 (250.70MB), cpu: 250.70M, memory: 0B, network: 0B} │ id_706 := 19:id:integer │ platform_source_715 := 28:platform_source:varchar │ created_on_699 := 12:created_on:timestamp(6) with time zone │ account_id_688 := 1:account_id:integer └─ LocalExchange[partitioning = HASH, arguments = [context_id_647::integer]] │ Layout: [context_id_647:integer, created_on_650:timestamp(6) with time zone] │ Estimates: {rows: 2977093 (51.10MB), cpu: 51.10M, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [61]] Layout: [context_id_647:integer, created_on_650:timestamp(6) with time zone] Fragment 61 [SOURCE] Output layout: [context_id_647, created_on_650] Output partitioning: BROADCAST [] TableScan[table = iceberg:sp_web.visits_visit$data@918499440402197125] Layout: [context_id_647:integer, created_on_650:timestamp(6) with time zone] Estimates: {rows: 2977093 (51.10MB), cpu: 51.10M, memory: 0B, network: 0B} context_id_647 := 12:context_id:integer created_on_650 := 15:created_on:timestamp(6) with time zone Fragment 62 [SOURCE] Output layout: [account_id_731, device_id] Output partitioning: HASH [account_id_731] ScanFilter[table = iceberg:sp_cw_user_data_engine.user_meta_info_accountmetadata$data@550938720318740374, dynamicFilters = {device_id = #df_17339}] Layout: [account_id_731:integer, device_id:varchar] Estimates: {rows: 7530135 (988.54MB), cpu: 988.54M, memory: 0B, network: 0B}/{rows: 7530135 (988.54MB), cpu: 988.54M, memory: 0B, network: 0B} device_id := 3:device_id:varchar account_id_731 := 1:account_id:integer Fragment 63 [SOURCE] Output layout: [customer_user_id, event_time, sp_created_at] Output partitioning: HASH [customer_user_id] ScanFilterProject[table = iceberg:mongo_marketing_attribution.appsflyer_event_data$data@2902615493133821655, filterPredicate = ((event_name IN (varchar 'af_demand_q1', varchar 'af_demand_q2', varchar 'af_demand_q3', varchar 'af_supply_l1', varchar 'af_supply_l2', varchar 'af_supply_l3', varchar 'install', varchar 're-attribution', varchar 're-engagement', varchar 'reinstall')) AND $like(app_name, LikePattern '[%Spinny%]'))] Layout: [customer_user_id:varchar, event_time:varchar, sp_created_at:timestamp(6) with time zone] Estimates: {rows: 338903622 (38.82GB), cpu: 57.76G, memory: 0B, network: 0B}/{rows: ? (?), cpu: 57.76G, memory: 0B, network: 0B}/{rows: ? (?), cpu: ?, memory: 0B, network: 0B} sp_created_at := 114:sp_created_at:timestamp(6) with time zone app_name := 12:app_name:varchar customer_user_id := 56:customer_user_id:varchar event_time := 69:event_time:varchar event_name := 64:event_name:varchar Fragment 64 [SOURCE] Output layout: [adset_760, campaign_779, customer_user_id_810, event_name_818, event_time_823, install_time_837, is_primary_attribution_840, is_retargeting_842, media_source_848, partner_856, platform_858, sp_created_at_868] Output partitioning: HASH [customer_user_id_810] TableScan[table = iceberg:mongo_marketing_attribution.appsflyer_event_data$data@2902615493133821655] Layout: [adset_760:varchar, campaign_779:varchar, customer_user_id_810:varchar, event_name_818:varchar, event_time_823:varchar, install_time_837:varchar, is_primary_attribution_840:varchar, is_retargeting_842:varchar, media_source_848:varchar, partner_856:varchar, platform_858:varchar, sp_created_at_868:timestamp(6) with time zone] Estimates: {rows: 338914598 (164.69GB), cpu: 164.69G, memory: 0B, network: 0B} event_time_823 := 69:event_time:varchar campaign_779 := 25:campaign:varchar customer_user_id_810 := 56:customer_user_id:varchar is_retargeting_842 := 88:is_retargeting:varchar event_name_818 := 64:event_name:varchar partner_856 := 102:partner:varchar install_time_837 := 83:install_time:varchar media_source_848 := 94:media_source:varchar adset_760 := 6:adset:varchar platform_858 := 104:platform:varchar sp_created_at_868 := 114:sp_created_at:timestamp(6) with time zone is_primary_attribution_840 := 86:is_primary_attribution:varchar Fragment 65 [HASH] Output layout: [id_966, expr_1133, adset_1139, campaign_1158, event_name_1197, event_time_1202, install_time_1216, is_primary_attribution_1219, is_retargeting_1221, media_source_1227, partner_1235, platform_1237] Output partitioning: HASH [id_966] InnerJoin[criteria = (device_id_993 = customer_user_id_1189), filter = ((CAST(sp_created_at_1247 AS date) >= date '2024-03-12') AND (expr_1312 <= CAST($operator$add(created_on_910, interval day to second '0 05:30:00.000') AS date))), distribution = PARTITIONED] │ Layout: [id_966:integer, expr_1133:date, adset_1139:varchar, campaign_1158:varchar, event_name_1197:varchar, event_time_1202:varchar, install_time_1216:varchar, is_primary_attribution_1219:varchar, is_retargeting_1221:varchar, media_source_1227:varchar, partner_1235:varchar, platform_1237:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 166.27GB, network: 0B} │ Distribution: PARTITIONED ├─ RemoteSource[sourceFragmentIds = [66]] │ Layout: [id_966:integer, device_id_993:varchar, created_on_910:timestamp(6) with time zone, expr_1133:date] └─ LocalExchange[partitioning = HASH, arguments = [customer_user_id_1189::varchar]] │ Layout: [adset_1139:varchar, campaign_1158:varchar, customer_user_id_1189:varchar, event_name_1197:varchar, event_time_1202:varchar, install_time_1216:varchar, is_primary_attribution_1219:varchar, is_retargeting_1221:varchar, media_source_1227:varchar, partner_1235:varchar, platform_1237:varchar, sp_created_at_1247:timestamp(6) with time zone, expr_1312:date] │ Estimates: {rows: 338914598 (166.27GB), cpu: 166.27G, memory: 0B, network: 0B} └─ Project[] │ Layout: [adset_1139:varchar, campaign_1158:varchar, customer_user_id_1189:varchar, event_name_1197:varchar, event_time_1202:varchar, install_time_1216:varchar, is_primary_attribution_1219:varchar, is_retargeting_1221:varchar, media_source_1227:varchar, partner_1235:varchar, platform_1237:varchar, sp_created_at_1247:timestamp(6) with time zone, expr_1312:date] │ Estimates: {rows: 338914598 (166.27GB), cpu: 166.27G, memory: 0B, network: 0B} │ expr_1312 := CAST($operator$add((CASE WHEN (length(trim(event_time_1202)) = bigint '0') THEN null::timestamp(3) WHEN $like(event_time_1202, LikePattern '[%T%]') THEN date_parse(event_time_1202, varchar(18) '%Y-%m-%dT%H:%i:%sZ') ELSE date_parse(event_time_1202, varchar(17) '%Y-%m-%d %H:%i:%s') END), interval day to second '0 05:30:00.000') AS date) └─ RemoteSource[sourceFragmentIds = [73]] Layout: [adset_1139:varchar, campaign_1158:varchar, customer_user_id_1189:varchar, event_name_1197:varchar, event_time_1202:varchar, install_time_1216:varchar, is_primary_attribution_1219:varchar, is_retargeting_1221:varchar, media_source_1227:varchar, partner_1235:varchar, platform_1237:varchar, sp_created_at_1247:timestamp(6) with time zone] Fragment 66 [HASH] Output layout: [id_966, device_id_993, created_on_910, expr_1133] Output partitioning: HASH [device_id_993] Project[] │ Layout: [id_966:integer, device_id_993:varchar, created_on_910:timestamp(6) with time zone, expr_1133:date] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ Aggregate[keys = [id_966, device_id_993, row_number_1132, created_on_910, expr_1133]] │ Layout: [id_966:integer, device_id_993:varchar, row_number_1132:bigint, created_on_910:timestamp(6) with time zone, expr_1133:date] │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} └─ FilterProject[filterPredicate = (row_number_1132 = bigint '1')] │ Layout: [created_on_910:timestamp(6) with time zone, id_966:integer, device_id_993:varchar, row_number_1132:bigint, expr_1133:date] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B}/{rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ expr_1133 := CAST($operator$add(created_on_959, interval day to second '0 05:30:00.000') AS date) └─ Project[] │ Layout: [created_on_910:timestamp(6) with time zone, created_on_959:timestamp(6) with time zone, id_966:integer, device_id_993:varchar, row_number_1132:bigint] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ TopNRanking[partitionBy = [id_966], orderBy = [event_time_1072 DESC NULLS LAST], limit = 1] │ Layout: [created_on_910:timestamp(6) with time zone, created_on_959:timestamp(6) with time zone, id_966:integer, device_id_993:varchar, event_time_1072:varchar, row_number_1132:bigint] │ row_number_1132 := ROW_NUMBER └─ LocalExchange[partitioning = HASH, arguments = [id_966::integer]] │ Layout: [created_on_910:timestamp(6) with time zone, created_on_959:timestamp(6) with time zone, id_966:integer, device_id_993:varchar, event_time_1072:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [67]] Layout: [created_on_910:timestamp(6) with time zone, created_on_959:timestamp(6) with time zone, id_966:integer, device_id_993:varchar, event_time_1072:varchar] Fragment 67 [HASH] Output layout: [created_on_910, created_on_959, id_966, device_id_993, event_time_1072] Output partitioning: HASH [id_966] TopNRanking[partitionBy = [id_966], orderBy = [event_time_1072 DESC NULLS LAST], limit = 1] │ Layout: [created_on_910:timestamp(6) with time zone, id_966:integer, created_on_959:timestamp(6) with time zone, device_id_993:varchar, event_time_1072:varchar] │ row_number_1132 := ROW_NUMBER └─ InnerJoin[criteria = (device_id_993 = customer_user_id_1059), filter = ((CAST($operator$add(created_on_910, interval day to second '0 05:30:00.000') AS date) >= date '2024-03-12') AND (CAST(sp_created_at_1117 AS date) >= date '2024-03-12') AND (expr_1313 <= CAST($operator$add(created_on_910, interval day to second '0 05:30:00.000') AS date))), distribution = PARTITIONED] │ Layout: [created_on_910:timestamp(6) with time zone, id_966:integer, created_on_959:timestamp(6) with time zone, device_id_993:varchar, event_time_1072:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: ?, network: 0B} │ Distribution: PARTITIONED │ dynamicFilterAssignments = {customer_user_id_1059 -> #df_17364} ├─ RemoteSource[sourceFragmentIds = [68]] │ Layout: [created_on_910:timestamp(6) with time zone, id_966:integer, created_on_959:timestamp(6) with time zone, device_id_993:varchar] └─ LocalExchange[partitioning = HASH, arguments = [customer_user_id_1059::varchar]] │ Layout: [customer_user_id_1059:varchar, event_time_1072:varchar, sp_created_at_1117:timestamp(6) with time zone, expr_1313:date] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} └─ Project[] │ Layout: [customer_user_id_1059:varchar, event_time_1072:varchar, sp_created_at_1117:timestamp(6) with time zone, expr_1313:date] │ Estimates: {rows: ? (?), cpu: ?, memory: 0B, network: 0B} │ expr_1313 := CAST($operator$add((CASE WHEN (length(trim(event_time_1072)) = bigint '0') THEN null::timestamp(3) WHEN $like(event_time_1072, LikePattern '[%T%]') THEN date_parse(event_time_1072, varchar(18) '%Y-%m-%dT%H:%i:%sZ') ELSE date_parse(event_time_1072, varchar(17) '%Y-%m-%d %H:%i:%s') END), interval day to second '0 05:30:00.000') AS date) └─ RemoteSource[sourceFragmentIds = [72]] Layout: [customer_user_id_1059:varchar, event_time_1072:varchar, sp_created_at_1117:timestamp(6) with time zone] Fragment 68 [HASH] Output layout: [created_on_910, id_966, created_on_959, device_id_993] Output partitioning: HASH [device_id_993] InnerJoin[criteria = (account_id_948 = account_id_991), distribution = PARTITIONED] │ Layout: [created_on_959:timestamp(6) with time zone, id_966:integer, created_on_910:timestamp(6) with time zone, device_id_993:varchar] │ Estimates: {rows: ? (?), cpu: ?, memory: 988.54MB, network: 0B} │ Distribution: PARTITIONED │ dynamicFilterAssignments = {account_id_991 -> #df_17366} ├─ RemoteSource[sourceFragmentIds = [69]] │ Layout: [account_id_948:integer, created_on_959:timestamp(6) with time zone, id_966:integer, created_on_910:timestamp(6) with time zone] └─ LocalExchange[partitioning = HASH, arguments = [account_id_991::integer]] │ Layout: [account_id_991:integer, device_id_993:varchar] │ Estimates: {rows: 7530135 (988.54MB), cpu: 988.54M, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [71]] Layout: [account_id_991:integer, device_id_993:varchar] Fragment 69 [SOURCE] Output layout: [account_id_948, created_on_959, id_966, created_on_910] Output partitioning: HASH [account_id_948] InnerJoin[criteria = (id_966 = context_id_907), distribution = REPLICATED] │ Layout: [account_id_948:integer, created_on_959:timestamp(6) with time zone, id_966:integer, created_on_910:timestamp(6) with time zone] │ Estimates: {rows: ? (?), cpu: ?, memory: 306.63MB, network: 0B} │ Distribution: REPLICATED │ dynamicFilterAssignments = {context_id_907 -> #df_17367} ├─ ScanFilterProject[table = iceberg:sp_web.buy_lead_buylead$data@1299828741364571249, filterPredicate = $like(platform_source_975, LikePattern '[%app_%]'), dynamicFilters = {account_id_948 = #df_17366, id_966 = #df_17367}] │ Layout: [account_id_948:integer, created_on_959:timestamp(6) with time zone, id_966:integer] │ Estimates: {rows: 12700031 (278.56MB), cpu: 349.15M, memory: 0B, network: 0B}/{rows: 11430028 (250.70MB), cpu: 349.15M, memory: 0B, network: 0B}/{rows: 11430028 (250.70MB), cpu: 250.70M, memory: 0B, network: 0B} │ account_id_948 := 1:account_id:integer │ id_966 := 19:id:integer │ created_on_959 := 12:created_on:timestamp(6) with time zone │ platform_source_975 := 28:platform_source:varchar └─ LocalExchange[partitioning = HASH, arguments = [context_id_907::integer]] │ Layout: [context_id_907:integer, created_on_910:timestamp(6) with time zone] │ Estimates: {rows: 2977093 (51.10MB), cpu: 51.10M, memory: 0B, network: 0B} └─ RemoteSource[sourceFragmentIds = [70]] Layout: [context_id_907:integer, created_on_910:timestamp(6) with time zone] Fragment 70 [SOURCE] Output layout: [context_id_907, created_on_910] Output partitioning: BROADCAST [] TableScan[table = iceberg:sp_web.visits_visit$data@918499440402197125] Layout: [context_id_907:integer, created_on_910:timestamp(6) with time zone] Estimates: {rows: 2977093 (51.10MB), cpu: 51.10M, memory: 0B, network: 0B} context_id_907 := 12:context_id:integer created_on_910 := 15:created_on:timestamp(6) with time zone Fragment 71 [SOURCE] Output layout: [account_id_991, device_id_993] Output partitioning: HASH [account_id_991] ScanFilter[table = iceberg:sp_cw_user_data_engine.user_meta_info_accountmetadata$data@550938720318740374, dynamicFilters = {device_id_993 = #df_17364}] Layout: [account_id_991:integer, device_id_993:varchar] Estimates: {rows: 7530135 (988.54MB), cpu: 988.54M, memory: 0B, network: 0B}/{rows: 7530135 (988.54MB), cpu: 988.54M, memory: 0B, network: 0B} device_id_993 := 3:device_id:varchar account_id_991 := 1:account_id:integer Fragment 72 [SOURCE] Output layout: [customer_user_id_1059, event_time_1072, sp_created_at_1117] Output partitioning: HASH [customer_user_id_1059] ScanFilterProject[table = iceberg:mongo_marketing_attribution.appsflyer_event_data$data@2902615493133821655, filterPredicate = ((event_name_1067 IN (varchar 'af_demand_q1', varchar 'af_demand_q2', varchar 'af_demand_q3', varchar 'af_supply_l1', varchar 'af_supply_l2', varchar 'af_supply_l3', varchar 'install', varchar 're-attribution', varchar 're-engagement', varchar 'reinstall')) AND $like(app_name_1015, LikePattern '[%Spinny%]'))] Layout: [customer_user_id_1059:varchar, event_time_1072:varchar, sp_created_at_1117:timestamp(6) with time zone] Estimates: {rows: 338903622 (38.82GB), cpu: 57.76G, memory: 0B, network: 0B}/{rows: ? (?), cpu: 57.76G, memory: 0B, network: 0B}/{rows: ? (?), cpu: ?, memory: 0B, network: 0B} event_name_1067 := 64:event_name:varchar app_name_1015 := 12:app_name:varchar sp_created_at_1117 := 114:sp_created_at:timestamp(6) with time zone customer_user_id_1059 := 56:customer_user_id:varchar event_time_1072 := 69:event_time:varchar Fragment 73 [SOURCE] Output layout: [adset_1139, campaign_1158, customer_user_id_1189, event_name_1197, event_time_1202, install_time_1216, is_primary_attribution_1219, is_retargeting_1221, media_source_1227, partner_1235, platform_1237, sp_created_at_1247] Output partitioning: HASH [customer_user_id_1189] TableScan[table = iceberg:mongo_marketing_attribution.appsflyer_event_data$data@2902615493133821655] Layout: [adset_1139:varchar, campaign_1158:varchar, customer_user_id_1189:varchar, event_name_1197:varchar, event_time_1202:varchar, install_time_1216:varchar, is_primary_attribution_1219:varchar, is_retargeting_1221:varchar, media_source_1227:varchar, partner_1235:varchar, platform_1237:varchar, sp_created_at_1247:timestamp(6) with time zone] Estimates: {rows: 338914598 (164.69GB), cpu: 164.69G, memory: 0B, network: 0B} platform_1237 := 104:platform:varchar sp_created_at_1247 := 114:sp_created_at:timestamp(6) with time zone media_source_1227 := 94:media_source:varchar event_time_1202 := 69:event_time:varchar adset_1139 := 6:adset:varchar customer_user_id_1189 := 56:customer_user_id:varchar campaign_1158 := 25:campaign:varchar install_time_1216 := 83:install_time:varchar is_primary_attribution_1219 := 86:is_primary_attribution:varchar partner_1235 := 102:partner:varchar event_name_1197 := 64:event_name:varchar is_retargeting_1221 := 88:is_retargeting:varchar Fragment 74 [SOURCE] Output layout: [display_name_1287, id_1289] Output partitioning: BROADCAST [] TableScan[table = iceberg:sp_web.address_city$data@3145091731273200997] Layout: [display_name_1287:varchar, id_1289:integer] Estimates: {rows: 454 (15.32kB), cpu: 15.32k, memory: 0B, network: 0B} display_name_1287 := 3:display_name:varchar id_1289 := 5:id:integer

@sachleen0700
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Query:
`with CTE as (
select
distinct T1.id,
T1.lead_date,
aps.event_name,
aps.campaign,
aps.media_source,
aps.platform,
aps.partner,
aps.is_primary_attribution,
aps.is_retargeting,
aps.adset,
case
WHEN LENGTH(TRIM(aps.event_time)) = 0 THEN NULL
when aps.event_time like '%T%' then date_parse(aps.event_time, '%Y-%m-%dT%H:%i:%sZ')
else date_parse(aps.event_time, '%Y-%m-%d %H:%i:%s')
end as event_time1,
aps.event_time,
ROW_NUMBER() OVER(
PARTITION BY T1.id
ORDER BY
aps.event_time DESC
) as rn_time_stamp,
case
when aps.event_name = 'af_demand_q3' then 3
when aps.event_name = 'af_demand_q2' then 2
when aps.event_name = 'af_demand_q1' then 1
else 0
end as event_name_no,
case
when aps.is_primary_attribution = 'true' then 1
else 0
end as is_primary_attribution_no,
case
when aps.is_retargeting = 'true' then 1
else 0
end as is_retargeting_no,
date (
case
WHEN LENGTH(TRIM(aps.install_time)) = 0 THEN NULL
when aps.install_time like '%T%' then date_parse(aps.install_time, '%Y-%m-%dT%H:%i:%sZ')
else date_parse(aps.install_time, '%Y-%m-%d %H:%i:%s')
end + interval '330' minute
) AS install_date
from
(
select
*
from
(
select
distinct bl.id,
acm.device_id,
aps.customer_user_id,
ROW_NUMBER() OVER(
PARTITION BY bl.id
ORDER BY
event_time DESC
) as rn_time_stamp,
v.created_on,
date(bl.created_on + interval '330' minute) lead_date
FROM
sp_web.visits_visit v
INNER JOIN sp_web.buy_lead_buylead bl ON bl.id = v.context_id
LEFT JOIN sp_cw_user_data_engine.user_meta_info_accountmetadata acm ON bl.account_id = acm.account_id
LEFT JOIN mongo_marketing_attribution.appsflyer_event_data aps ON acm.device_id = aps.customer_user_id
where
DATE(v.created_on + interval '330' minute) >= current_date - interval '65' day
and date(aps.sp_created_at) >= current_date - interval '65' day
and bl.platform_source like '%app_%'
and aps.app_name like '%Spinny%'
and aps.event_name in (
'af_demand_q3',
'af_demand_q1',
'af_demand_q2',
'af_supply_l3',
'af_supply_l2',
'af_supply_l1',
'reinstall',
'install',
're-engagement',
're-attribution'
)
and date(
(
case
WHEN LENGTH(TRIM(aps.event_time)) = 0 THEN NULL
when aps.event_time like '%T%' then date_parse(aps.event_time, '%Y-%m-%dT%H:%i:%sZ')
else date_parse(aps.event_time, '%Y-%m-%d %H:%i:%s')
end
) + interval '330' minute
) <= date(v.created_on + interval '330' minute)
)
where
rn_time_stamp = 1
) T1
LEFT JOIN mongo_marketing_attribution.appsflyer_event_data aps ON T1.customer_user_id = aps.customer_user_id
and date(
(
case
WHEN LENGTH(TRIM(aps.event_time)) = 0 THEN NULL
when aps.event_time like '%T%' then date_parse(aps.event_time, '%Y-%m-%dT%H:%i:%sZ')
else date_parse(aps.event_time, '%Y-%m-%d %H:%i:%s')
end
) + interval '330' minute
) <= date(T1.created_on + interval '330' minute)
where
date(aps.sp_created_at) >= current_date - interval '65' day
)
select distinct
city,
Start_date,
Case
when utm_medium = 'truebil' Then 'truebil'
when utm_source = 'truebil' Then 'truebil'
when utm_term = 'TruebilBudgetRedirect' Then 'truebil'
when CAST(app.app_id AS VARCHAR) = CAST(V1.context_id AS VARCHAR) then app.App_Channel
when utm_source = 'direct'
and utm_medium is null Then 'Direct'
when utm_source = 'direct'
and utm_medium = '' Then 'Direct'
when utm_source in ('organic')
and utm_medium = '' then 'Organic'
when utm_source in ('organic')
and utm_medium is null then 'Organic'
when utm_source = ''
and utm_medium = '' then 'Organic'
when utm_source is null
and utm_medium is null then 'Organic'
when utm_medium = 'fbad' Then 'Facebook'
when utm_medium = 'FBboost' Then 'Facebook'
when utm_medium = 'cpm' Then 'Facebook'
when utm_medium = 'affiliate_demand' Then 'Affiliate'
when utm_source in ('Taboola', 'adgebra', 'outbrain') Then 'Native'
when utm_medium = 'partnerships' Then 'Partnerships'
when utm_medium in (
'gads_t_search',
'gads_c_search',
'gads_m_search',
'bingads_c_search',
'bingads_m_search',
'bingads_t_search'
)
and utm_source like '%Brand%' Then 'SEM Brand'
when utm_medium in (
'gads_t_search',
'gads_c_search',
'gads_m_search',
'bingads_c_search',
'bingads_m_search',
'bingads_t_search'
)
and utm_source not like '%Brand%' Then 'SEM Non Brand'
when utm_medium like '%whatsapp%'
or utm_medium like '%sms%'
or utm_medium like '%push%'
or utm_medium like '%whatsapp=utm_campaign=supply-lead-created_abn1nkm%'
or utm_medium like '%webpush%'
or utm_medium like '%WhatsappGetDetailsTD%'
or utm_medium like '%whatsapp_promotional%'
or utm_medium like '%email%'
or utm_source like '%whatsapp_share%' Then 'CRM'
when utm_medium = 'gads_t_video' Then 'Youtube'
when utm_medium = 'gads_c_video' Then 'Youtube'
when utm_medium = 'gads_m_video' Then 'Youtube'
when utm_medium = 'gads_m_discovery' Then 'Discovery'
when utm_medium = 'gads_t_discovery' Then 'Discovery'
when utm_medium = 'gads_c_discovery' Then 'Discovery'
when utm_medium = 'gads_t_display' Then 'Display'
when utm_medium = 'gads_c_display' Then 'Display'
when utm_medium = 'gads_m_display' Then 'Display'
when utm_medium = 'affiliate' Then 'Supply_Affiliate'
else 'Others'
end as utmmedium,
Case
when utm_medium in (
'fbad',
'FBboost',
'gads_m_display',
'gads_c_display',
'gads_t_display',
'gads_m_video',
'gads_c_video',
'gads_t_video',
'gads_c_discovery',
'gads_t_discovery',
'gads_m_discovery'
)
and utm_source like '%RM%' Then 'RM'
when utm_medium in (
'fbad',
'FBboost',
'gads_m_display',
'gads_c_display',
'gads_t_display',
'gads_m_video',
'gads_c_video',
'gads_t_video',
'gads_c_discovery',
'gads_t_discovery',
'gads_m_discovery'
)
and utm_source not like '%RM%' Then 'PR'
when utm_source like '%Remarketing%' Then 'RM'
when utm_medium = 'email' Then 'email'
when utm_medium = 'sms' Then 'sms'
when utm_medium = 'webpush' Then 'Webpush'
when utm_medium = 'push' Then 'Push'
when utm_medium = 'whatsapp' Then 'Whatsapp'
when utm_medium = 'affiliate_demand' Then 'Website'
when camp_id in (
473,
1027,
1028,
1029,
1050,
1051,
1052,
1054,
1055,
1056,
1057
) then 'MissedCall'
when utm_source = 'truebil' Then 'truebil'
else 'Others'
end as utmsource,
platform,
case
when utm_source like '%SPS%'
or utm_source like '%SPMS%'
or utm_medium = 'affiliate' then 'Cross LOB'
else 'Same LOB'
end as LOB,
case
when Source2 IN ('buy_request', 'buyrequest') then 'buyrequest'
when Source2 IN ('car_finance', 'carfinance') then 'carfinance'
when lower(Source2) like '%callback%' then 'callback'
when Source2 IN ('contact_us', 'contactus') then 'contactus'
when Source2 IN ('deal_requested', 'dealrequest') then 'dealrequest'
when lower(Source2) like '%direct%' then 'direct'
when lower(Source2) like '%facebookleadform%' then 'facebookleadform'
when lower(Source2) like '%filters%' then 'neutralpage'
when lower(Source2) like '%neutral%' then 'neutralpage'
when Source2 IN ('filters', 'neutral_page') then 'neutralpage'
when lower(Source2) like '%googleleadform%' then 'googleleadform'
when lower(Source2) like '%lead%' then 'lead'
when Source2 IN ('message', 'whatsapp') then 'message'
when Source2 IN ('notify_me', 'notifyme') then 'notifyme'
when lower(Source2) like '%proxycontextmodel%' then 'proxycontextmodel'
when lower(Source2) like '%reference%' then 'reference'
when lower(Source2) like '%sell_to_buy_lead%' then 'lead'
when lower(Source2) like '%shortlist%' then 'shortlist'
when Source2 IN ('viewinspectionreport', 'view_inspection_report') then 'viewinspectionreport'
when lower(Source2) like '%webarticle%' then 'webarticle'
when Source2 IN (
'PDP_PhotoGallery_360',
'PDP_PhotoGallery_AllPhotos'
) then 'imagegallery'
when source2 = 'user_activity_log'
and user_activity_type = 'view_inspection_report' then 'viewinspectionreport'
when source2 = 'user_activity_log'
and user_activity_type = 'view_more_car_images' then 'imagegallery'
when Source2 is null then 'null'
else Source2
end as Source2,
Source_Category,
Assigned_lead_CT,
Walkin_type,
app.app_id,
V1.context_id
from
(
SELECT
*,
case
when SOURCE = 'hub' then 'hub'
when SOURCE in ('Olx', 'CarDekho', 'CarTrade') then 'Offline'
else 'Online'
end as Source_Category
FROM
(
SELECT
DISTINCT v.id AS visit_id,
v.context_id,
ual.user_activity_type,
EXTRACT(
day
FROM
DATE(visit_start_time + interval '330' minute)
) AS start_day,
DATE(visit_start_time + interval '330' minute) start_date,
DATE(visit_start_time + interval '330' minute) start_time,
no_of_testdrives,
ac.display_name,
case
when b.platform_source like '%app%' THEN 'App'
when b.platform_source like '%web%' THEN 'Web'
when b.platform_source like '%mweb%' THEN 'Web'
else 'Others'
end as platform,
null as camp_id,
t4.source,
case
when min_cta_slug is not null then min_cta_slug
else (
case
when b.sub_source = 'neutral_page' then 'neutral_page'
else t4.source
end
)
end as source2,
utm_source,
utm_medium,
utm_term,
CASE
WHEN at_home = 1 THEN 'HTD'
ELSE 'HV'
END AS Walkin_type,
CASE
WHEN tag_status = 'available' THEN 'Available'
WHEN tag_status = 'available-&-booked' THEN 'Booked'
WHEN tag_status = 'available-&-in-refurb' THEN 'In refurb'
WHEN tag_status = 'available-&-booked-&-in-refurb' THEN 'Booked & In Refurb'
WHEN tag_status = 'booked' THEN 'Booked'
WHEN tag_status = 'in-refurb' THEN 'In Refurb'
WHEN tag_status = 'upcoming-supply' THEN 'Upcoming Supply'
WHEN tag_status = 'sold' THEN 'Sold'
else null
end as Car_status,
registration_no,
ROW_NUMBER() OVER (
PARTITION BY v.context_id
ORDER BY
visit_start_time asc
) AS VISIT_NUMBER,
case
when ac.display_name like '%Delhi%' then 'NCR'
when ac.display_name like '%Bangalore%' then 'Bangalore'
when ac.display_name like '%Hyderabad%' then 'Hyderabad'
when ac.display_name like '%Gurgaon%' then 'NCR'
when ac.display_name like '%Punee%' then 'Pune'
when ac.display_name like '%Mumbai%' then 'Mumbai'
when ac.display_name like '%Delhi/Delhi NCR%' then 'NCR'
when ac.display_name like '%Ahmedabad%' then 'Ahmedabad'
when ac.display_name like '%Noida%' then 'NCR'
when ac.display_name like '%Chennai%' then 'Chennai'
when ac.display_name like '%Lucknow%' then 'Lucknow'
when ac.display_name like '%Kolkata%' then 'Kolkata'
when ac.display_name like '%Ghaziabad%' then 'NCR'
when ac.display_name like '%Faridabad%' then 'NCR'
when ac.display_name like '%Jaipur%' then 'Jaipur'
when ac.display_name like '%Indore%' then 'Indore'
when ac.display_name like '%Mysore%' then 'Bangalore'
when ac.display_name like '%Coimbatore%' then 'Coimbatore'
when ac.display_name like '%Chandigarh%' then 'Chandigarh'
when ac.display_name like '%Rewari%' then 'NCR'
when ac.display_name like '%Ambala%' then 'Chandigarh'
when ac.display_name like '%Hubli%' then 'Bangalore'
when ac.display_name like '%Panipat%' then 'NCR'
when ac.display_name like '%Greater Noida%' then 'NCR'
when ac.display_name like '%Rohtak%' then 'NCR'
when ac.display_name like '%Meerut%' then 'NCR'
when ac.display_name like '%Karnal%' then 'NCR'
when ac.display_name like '%Sonipat%' then 'NCR'
when ac.display_name like '%Kanpur%' then 'Lucknow'
when ac.display_name like '%Mangalore%' then 'Bangalore'
when ac.display_name like '%Surat%' then 'Surat'
when ac.display_name like '%Aligarh%' then 'NCR'
when ac.display_name like '%Belgaum%' then 'Bangalore'
when ac.display_name like '%Hassan%' then 'Bangalore'
when ac.display_name like '%Jammu%' then 'NCR'
when ac.display_name like '%Jhajjar%' then 'NCR'
when ac.display_name like '%Agra%' then 'NCR'
when ac.display_name like '%Bhiwadi%' then 'Jaipur'
when ac.display_name like '%Kolar%' then 'Bangalore'
when ac.display_name like '%Gulbarga%' then 'Bangalore'
when ac.display_name like '%Warangal%' then 'Hyderabad'
when ac.display_name like '%Raichur%' then 'Bangalore'
when ac.display_name like '%Alwar%' then 'NCR'
when ac.display_name like '%Nashik%' then 'Pune'
when ac.display_name like '%Bahadurgarh%' then 'NCR'
when ac.display_name like '%Mathura%' then 'NCR'
when ac.display_name like '%Sirsa%' then 'Chandigarh'
when ac.display_name like '%Thane%' then 'Mumbai'
when ac.display_name like '%Nagpur%' then 'Pune'
when ac.display_name like '%Moradabad%' then 'Lucknow'
when ac.display_name like '%Karimnagar%' then 'Hyderabad'
when ac.display_name like '%Amritsar%' then 'Chandigarh'
when ac.display_name like '%Patna%' then 'Lucknow'
when ac.display_name like '%Bagalkot%' then 'Bangalore'
when ac.display_name like '%Kochi%' then 'Kochi'
when ac.display_name like '%Jhansi%' then 'Lucknow'
when ac.display_name like '%Nizamabad%' then 'Hyderabad'
when ac.display_name like '%Bareilly%' then 'Lucknow'
when ac.display_name like '%Saharanpur%' then 'Lucknow'
when ac.display_name like '%Navi Mumbai%' then 'Mumbai'
when ac.display_name like '%Jodhpur%' then 'Jaipur'
when ac.display_name like '%Gwalior%' then 'Indore'
when ac.display_name like '%Hapur%' then 'NCR'
when ac.display_name like '%Bhopal%' then 'Indore'
when ac.display_name like '%Dehradun%' then 'NCR'
when ac.display_name like '%Kurukshetra%' then 'Chandigarh'
when ac.display_name like '%Ahmednagar%' then 'Pune'
when ac.display_name like '%Mandya%' then 'Bangalore'
when ac.display_name like '%Aurangabad%' then 'Pune'
when ac.display_name like '%Jalandhar%' then 'Chandigarh'
when ac.display_name like '%Gorakhpur%' then 'Lucknow'
when ac.display_name like '%Khammam%' then 'Hyderabad'
when ac.display_name like '%Muzaffarnagar%' then 'NCR'
when ac.display_name like '%Rajkot%' then 'Ahmedabad'
when ac.display_name like '%Varanasi%' then 'Lucknow'
when ac.display_name like '%Hosur%' then 'Coimbatore'
when ac.display_name like '%Allahabad%' then 'Lucknow'
when ac.display_name like '%Bathinda%' then 'Chandigarh'
when ac.display_name like '%Solapur%' then 'Pune'
when ac.display_name like '%Vadodara%' then 'Ahmedabad'
when ac.display_name like '%tumkur%' then 'Bangalore'
when ac.display_name like '%tumakuru%' then 'Bangalore'
when ac.display_name like '%shimoga%' then 'Bangalore'
when ac.display_name like '%Shivamogga%' then 'Bangalore'
when ac.display_name like '%Navi Mumbai%' then 'Mumbai'
when ac.display_name like '%Navsari%' then 'Ahmedabad'
when ac.display_name like '%Pune%' then 'Pune'
when ac.display_name like '%sangli%' then 'Pune'
when ac.display_name like '%Bhavnagar%' then 'Ahmedabad'
when ac.display_name like '%Surat%' then 'Surat'
else ac.display_name
end as city,
case
when su.full_name IS NOT NULL Then 'Assigned'
else 'Not_Assigned'
end as Assigned_lead_CT
FROM
sp_web.visits_visit v
INNER JOIN sp_web.buy_lead_buylead b ON b.id = v.context_id
LEFT JOIN(
SELECT
context_id,
assigned_to_id,
created_time
FROM
(
SELECT
context_id,
assigned_to_id,
created_time,
ROW_NUMBER() OVER(
PARTITION BY CONTEXT_ID
ORDER BY
created_time DESC
) as Running_count
FROM
sp_web.workflow_usertask wu
INNER JOIN sp_web.spinny_auth_user_groups sau on sau.user_id = wu.assigned_to_id
WHERE
group_id IN (132, 206)
) sau
WHERE
Running_count = 1
) sau on sau.context_id = b.id
LEFT JOIN sp_web.spinny_auth_user su ON su.id = sau.assigned_to_id
LEFT JOIN sp_phonecall.call_logs ph on b.account_id = ph.account_id
left join (
SELECT
t3.id,
CASE
WHEN t3.final_source = 'www.olx.in' THEN 'Olx'
WHEN t3.final_source = 'www.cardekho.com' THEN 'CarDekho'
WHEN t3.final_source = 'www.cartrade.com' THEN 'CarTrade'
ELSE t3.final_source
END AS SOURCE
FROM(
SELECT
t2.id,
t2.source_object_type_id,
CASE
WHEN t2.source_object_type_id = 321 THEN t2.exbr
WHEN t2.source_object_type_id = 246
AND t2.url = 'Direct' then 'direct'
WHEN t2.source_object_type_id = 319 THEN t2.platform
WHEN t2.source_object_type_id = 322 THEN t2.platform
ELSE t2.model
END AS final_source,
t2.url
FROM(
SELECT
b.id,
b.source,
b.source_object_id,
b.source_object_type_id,
dct.model,
elp.display_name AS platform,
lpa.display_name AS account,
t1.display_name AS exbr,
ww.title,
ww.url
FROM
sp_web.buy_lead_buylead b
LEFT JOIN sp_web.django_content_type dct ON b.source_object_type_id = dct.id
left join sp_web.whatsapp_message wh on b.source_object_id = wh.id
LEFT JOIN sp_web.external_listing_listingplatformaccounts lpa ON lpa.id = b.source_object_id
AND b.source_object_type_id IN (322, 319)
LEFT JOIN sp_web.external_listing_externallistingplatform elp ON lpa.platform_id = elp.id
AND b.source_object_type_id IN (322, 319)
LEFT JOIN(
SELECT
b.id,
b.source_object_type_id,
b.source_object_id,
elp.display_name
FROM
sp_web.buy_lead_buylead b
LEFT JOIN sp_web.external_listing_externalbuyrequest eb ON eb.id = b.source_object_id
AND b.source_object_type_id = 321
LEFT JOIN sp_web.external_listing_externallisting el ON el.id = eb.listing_id
LEFT JOIN sp_web.external_listing_listingplatformaccounts lpa ON lpa.id = el.account_id
LEFT JOIN sp_web.external_listing_externallistingplatform elp ON lpa.platform_id = elp.id
) t1 ON t1.id = b.id
LEFT JOIN sp_web.webresults_webarticle ww ON b.source_object_id = ww.id
AND b.source_object_type_id = 246
WHERE
DATE(b.created_on + interval '330' minute) >= date('2018-01-30')
) t2
) t3
) t4 on t4.id = b.id
left join (
select
T1.id,
case
when T1.id = t2.id then T2.min_ma_id
else T1.min_ma_id
end as min_ma_id,
T1.min_cta_slug
from
(
select
distinct id,
min_ma_id,
min_cta_slug
from
(
select
BL.id,
cta.marketing_attribution_id min_ma_id,
cta.cta_slug min_cta_slug,
row_number () over(
partition by cta.buy_lead_id
order by
log_creation_time
) as rn_min,
cta.log_creation_time min_log_creation_time
from
sp_web.buy_lead_buylead bl
LEFT JOIN mongo_marketing_attribution.buy_lead_cta_logs cta on cta.buy_lead_id = BL.id
left join sp_web.visits_visit vv on bl.id = vv.context_id
left join sp_web.spinny_auth_user au on au.id = vv.created_by_id
) T1
where
rn_min = 1
) T1
left join (
select
T2.ID,
min(T2.min_ma_id) as min_ma_id,
T2.min_cta_slug
from
(
select
T1.ID,
T1.min_ma_id,
T1.min_cta_slug
from
(
select
BL.id,
cta.marketing_attribution_id min_ma_id,
cta.cta_slug min_cta_slug,
row_number () over(
partition by cta.buy_lead_id
order by
cta.log_creation_time
) as rn_min,
cta.log_creation_time min_log_creation_time,
case
when vv.visit_type_id = 2
and bl.category = 'assured'
and au.is_staff = 0
and cta.cta_slug = 'buy_request' then 1
else 0
end as Buy_request
from
sp_web.buy_lead_buylead bl
LEFT JOIN mongo_marketing_attribution.buy_lead_cta_logs cta on cta.buy_lead_id = BL.id
left join sp_web.visits_visit vv on bl.id = vv.context_id
left join sp_web.spinny_auth_user au on au.id = vv.created_by_id
) T1
where
Buy_request = 1
) T2
group by
1,
3
) T2 on T1.id = T2.id
) cta on b.id = cta.id
left join sp_web.marketing_marketingattribution MM on MM.id = cta.min_ma_ID
left join sp_cw_user_data_engine.user_activity_logger_useractivitylog ual on ual.marketing_attribution_id = mm.id
LEFT JOIN sp_web.address_hub ah ON ah.id = v.hub_id
LEFT JOIN sp_web.address_city ac ON ac.id = b.city_id
LEFT JOIN sp_web.buy_lead_testdrive blt ON blt.visit_id = v.id
LEFT JOIN sp_web.listing_lead ll ON ll.id = blt.sell_lead_id
LEFT JOIN sp_web.listing_leadprofile lp ON lp.id = ll.profile_id
LEFT JOIN sp_web.status_status ss ON ss.id = v.status_id
WHERE
DATE(visit_start_time + interval '330' minute) >= DATE_TRUNC('month', current_date - interval '4' month)
AND b.category = 'assured'
AND ss.description NOT LIKE '%Cancel%'
) v
WHERE
DATE(start_date) >= CURRENT_DATE - interval '65' day
AND VISIT_NUMBER = 1
) V1
left join (
SELECT
distinct app_id ,
case
when channel = '591918414' then 'App_Affiliates'
when channel = '{offer_ref_id}' then 'App_Affiliates'
when channel = '3dot14' then 'App_Affiliates'
when channel = 'acemediaplus_int' then 'App_Affiliates'
when channel = 'adapptmobi' then 'App_Affiliates'
when channel = 'adcanopus' then 'App_Affiliates'
when channel = 'adcanopus_int' then 'App_Affiliates'
when channel = 'adcountryindia' then 'App_Affiliates'
when channel = 'adcountymedia_int' then 'App_Affiliates'
when channel = 'adpiece_int' then 'App_Affiliates'
when channel = 'adsvmedia_int' then 'App_Affiliates'
when channel = 'affinityveve' then 'App_Affiliates'
when channel = 'affleagency' then 'App_Affiliates'
when channel = 'amazus_int' then 'App_Affiliates'
when channel = 'appfloodaff_int' then 'App_Affiliates'
when channel = 'appitate_int' then 'App_Affiliates'
when channel = 'applabs_int' then 'App_Affiliates'
when channel = 'applabsmedia' then 'App_Affiliates'
when channel = 'appmontize' then 'App_Affiliates'
when channel = 'Appmontize1' then 'App_Affiliates'
when channel = 'appnext_int' then 'App_Affiliates'
when channel = 'atmoicads_int' then 'App_Affiliates'
when channel = 'backgardon_int' then 'App_Affiliates'
when channel = 'betop_int' then 'App_Affiliates'
when channel = 'blueocean_int' then 'App_Affiliates'
when channel = 'cheeringads_int' then 'App_Affiliates'
when channel = 'cooins_int' then 'App_Affiliates'
when channel = 'CRM' then 'App_CRM'
when channel = 'dech_int' then 'App_Affiliates'
when channel = 'dehheit_int' then 'App_Affiliates'
when channel = 'digitalverse_int' then 'App_Affiliates'
when channel = 'erinlabs' then 'App_Affiliates'
when channel = 'Facebook Ads' then 'App_Facebook'
when channel = 'gads_int' then 'App_Affiliates'
when channel = 'glance_int' then 'App_Affiliates'
when channel = 'googleadwords_int' then 'App_Google'
when channel = 'gourdmobiads_int' then 'App_Affiliates'
when channel = 'hasoffers_int' then 'App_Affiliates'
when channel = 'Hotstar' then 'App_Hotstar'
when channel = 'Hotstar' then 'App_Hotstar'
when channel = 'icolorfast_int' then 'App_Affiliates'
when channel = 'icubeswire' then 'App_Affiliates'
when channel = 'inmobi_int' then 'App_Affiliates'
when channel = 'inmobiagency' then 'App_Affiliates'
when channel = 'intellect_ads' then 'App_Affiliates'
when channel = 'intellectads' then 'App_Affiliates'
when channel = 'jumboads' then 'App_Affiliates'
when channel = 'kickcash_int' then 'App_Affiliates'
when channel = 'linmobi_int' then 'App_Affiliates'
when channel = 'livetopmedia_int' then 'App_Affiliates'
when channel = 'madcube_int' then 'App_Affiliates'
when channel = 'maopumedia_int' then 'App_Affiliates'
when channel = 'marlinads_int' then 'App_Affiliates'
when channel = 'mediaversedigis' then 'App_Affiliates'
when channel = 'mediaxpediatech' then 'App_Affiliates'
when channel = 'mobavenue' then 'App_Affiliates'
when channel = 'mobfountain2' then 'App_Affiliates'
when channel = 'mobpine_int' then 'App_Affiliates'
when channel = 'mobuppagency' then 'App_Affiliates'
when channel = 'mobupps_int' then 'App_Affiliates'
when channel = 'mobuppsagency' then 'App_Affiliates'
when channel = 'mobwide_int' then 'App_Affiliates'
when channel = 'mocaglobal' then 'App_Affiliates'
when channel = 'multiads_int' then 'App_Affiliates'
when channel = 'oneenginemedia' then 'App_Affiliates'
when channel = 'Organic' then 'App_Organic'
when channel = 'orilmobi_int' then 'App_Affiliates'
when channel = 'plusgamesgo_int' then 'App_Affiliates'
when channel = 'poche_int' then 'App_Affiliates'
when channel = 'pokktmkt' then 'App_Affiliates'
when channel = 'pokktperformance_int' then 'App_Affiliates'
when channel = 'prodigital' then 'App_Affiliates'
when channel = 'profuseservices_int' then 'App_Affiliates'
when channel = 'QR_code' then 'App_Affiliates'
when channel = 'QR_code' then 'App_Affiliates'
when channel = 'restricted' then 'App_Affiliates'
when channel = 'restricted' then 'App_Affiliates'
when channel = 'royomobi_int' then 'App_Affiliates'
when channel = 'seikoads_int' then 'App_Affiliates'
when channel = 'sharechat_int' then 'App_Affiliates'
when channel = 'siftco_int' then 'App_Affiliates'
when channel = 'simplyverses_int' then 'App_Affiliates'
when channel = 'Spinny' then 'App_Affiliates'
when channel = 'Spinny_Affle_PanIndia' then 'App_Affiliates'
when channel = 'Spinny_Android' then 'App_Affiliates'
when channel = 'Spotify' then 'App_Affiliates'
when channel = 'starrytech_int' then 'App_Affiliates'
when channel = 'surfertech_int' then 'App_Affiliates'
when channel = 'taboola_int' then 'App_Affiliates'
when channel = 'Tarsan' then 'App_Affiliates'
when channel = 'tempoads_int' then 'App_Affiliates'
when channel = 'test' then 'App_Affiliates'
when channel = 'test_fb_ak' then 'App_Affiliates'
when channel = 'tjzymob_int' then 'App_Affiliates'
when channel = 'TVF_Youtube' then 'App_Affiliates'
when channel = 'upsflyer_int' then 'App_Affiliates'
when channel = 'vcommission' then 'App_Affiliates'
when channel = 'verseiume_int' then 'App_Affiliates'
when channel = 'vestaapps_int' then 'App_Affiliates'
when channel = 'vidmobads_int' then 'App_Affiliates'
when channel = 'vserv' then 'App_Affiliates'
when channel = 'WhatsApp' then 'App_Whatsapp'
when channel = 'xyadsagency' then 'App_Affiliates'
when channel = 'axismobi' then 'App_Affiliates'
when channel = 'adzealous' then 'App_Affiliates'
when channel = 'econnectmobi' then 'App_Affiliates'
when channel = 'applabsmedia' then 'App_Affiliates'
when channel = 'magixengage' then 'App_Affiliates'
when channel = 'Auto-Car-Video' then 'App_Affiliates'
when channel = 'fillymedia' then 'App_Affiliates'
when channel = 'quickadsmedia' then 'App_Affiliates'
when channel = 'inmobidsp_int' then 'App_Affiliates'
when channel = 'blendaidigital' then 'App_Affiliates'
when channel = 'Apple Search Ads' then 'App_Affiliates'
when channel = 'ballyhoomedia' then 'App_Affiliates'
when channel = 'nativemonetize' then 'App_Affiliates'
when channel = 'Appnext' then 'App_Affiliates'
when channel = 'Email' then 'App_CRM'
when channel = 'Social_instagram' then 'App_Affiliates'
when channel = 'mobavenue_int' then 'App_Affiliates'
when channel = 'Survey' then 'App_CRM'
when channel = 'lucrative' then 'App_Affiliates'
when channel = 'aimarkit' then 'App_Affiliates'
when channel = 'flickstree' then 'App_Affiliates'
when channel = 'GlobalWideMedia' then 'App_Affiliates'
when channel = 'geoadmedia_int' then 'App_Affiliates'
when channel = 'globalwide_int' then 'App_Affiliates'
when channel = 'mobisaturntechn' then 'App_Affiliates'
when channel = 'mrndigital' then 'App_Affiliates'
when channel = 'unilead_network' then 'App_Affiliates'
when channel = 'optimidea' then 'App_Affiliates'
when channel = 'zorkanetwork' then 'App_Affiliates'
else 'App_organic'
end as App_Channel,
campaign2,
adset
from
(
SELECT
distinct b.id app_id,
case
when b.platform_source like '%app_%' THEN 'App'
when b.platform_source like '%web%' THEN 'Web'
when b.platform_source like '%mweb_%' THEN 'Web'
else 'Others'
end as platform,
case
when s_aps.campaign like '%_RM%' then 'RM'
when s_aps.campaign like '%PR%' then 'PR'
else null
end as Campaign,
s_aps.platform as Platform2,
s_aps.partner as partner,
display_name as city,
s_aps.media_source as media_source,
case
when s_aps.partner = '' then s_aps.media_source
else s_aps.partner
end as channel,
s_aps.install_date as install_date,
s_aps.adset as adset,
s_aps.campaign as campaign2
FROM
sp_web.visits_visit v
INNER JOIN sp_web.buy_lead_buylead b ON b.id = v.context_id
LEFT JOIN (
select
COALESCE(Q3.id, Non_Q3.id) AS id,
COALESCE(Q3.event_name, Non_Q3.event_name) AS event_name,
COALESCE(Q3.campaign, Non_Q3.campaign) AS campaign,
COALESCE(Q3.media_source, Non_Q3.media_source) AS media_source,
COALESCE(Q3.partner, Non_Q3.partner) AS partner,
COALESCE(Q3.platform, Non_Q3.platform) AS platform,
COALESCE(Q3.install_date, Non_Q3.install_date) AS install_date,
COALESCE(Q3.adset, Non_Q3.adset) AS adset
from
(
select
id,
event_name,
campaign,
date_event_time,
media_source,
partner,
platform,
install_date,
adset
from
(
select
id,
event_name,
campaign,
date(event_time1) date_event_time,
media_source,
partner,
platform,
install_date,
adset,
row_number () over (
partition by id
order by
event_time desc
) as rn_event_time_adset
from
(
select
*,
row_number () over (
partition by id
order by
event_time desc
) as rn_event_time
from
(
select
*
from
(
select
*,
dense_rank () over (
partition by id
order by
sum desc
) as dr_sum
from
(
select
*
from
(
select
id,
lead_date,
event_name,
campaign,
event_time,
event_time1,
media_source,
partner,
platform,
install_date,
adset,
max(event_name_no) event_name_no,
max(is_primary_attribution_no) is_primary_attribution_no,
max(is_retargeting_no) is_retargeting_no,
(
max(event_name_no) + max(is_primary_attribution_no) + max(is_retargeting_no)
) AS sum,
dense_rank () over (
partition by id
order by
max(event_name_no) desc
) as dr_event_name_no
from
CTE
group by
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11
)
where
dr_event_name_no = 1
)
)
where
dr_sum = 1
)
)
where
rn_event_time = 1
)
where
rn_event_time_adset = 1
) Non_Q3 full
join (
select
id,
event_name,
campaign,
date_event_time,
media_source,
partner,
platform,
install_date,
adset
from
(
select
id,
event_name,
campaign,
date(event_time1) date_event_time,
media_source,
partner,
platform,
install_date,
adset,
row_number () over (
partition by id
order by
event_time desc
) as rn_event_time_adset
from
(
select
*,
row_number () over (
partition by id
order by
event_time desc
) as rn_event_time
from
(
select
*
from
(
select
*,
dense_rank () over (
partition by id
order by
sum desc
) as dr_sum
from
(
select
*
from
(
select
id,
lead_date,
event_name,
campaign,
event_time,
event_time1,
media_source,
partner,
platform,
install_date,
adset,
max(event_name_no) event_name_no,
max(is_primary_attribution_no) is_primary_attribution_no,
max(is_retargeting_no) is_retargeting_no,
(
max(event_name_no) + max(is_primary_attribution_no) + max(is_retargeting_no)
) AS sum,
dense_rank () over (
partition by id
order by
max(event_name_no) desc
) as dr_event_name_no
from
CTE
where
event_name = 'af_demand_q3'
group by
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11
)
where
dr_event_name_no = 1
)
)
where
dr_sum = 1
)
)
where
rn_event_time = 1
)
where
rn_event_time_adset = 1
) Q3 on Non_Q3.id = Q3.id
) s_aps on s_aps.id = b.id
LEFT JOIN sp_web.address_city ac ON ac.id = b.city_id
WHERE
DATE(v.created_on + interval '330' minute) >= current_date - interval '65' day
and b.category = 'assured'
and b.platform_source like '%app%'
)
) app on cast(app.app_id as varchar) = cast(v1.context_id as varchar)

ORDER BY
start_date desc

limit 100
`

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iceberg Iceberg connector
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@sachleen0700 @findinpath