Return-Path: X-Original-To: apmail-hive-dev-archive@www.apache.org Delivered-To: apmail-hive-dev-archive@www.apache.org Received: from mail.apache.org (hermes.apache.org [140.211.11.3]) by minotaur.apache.org (Postfix) with SMTP id 94ECCF5A7 for ; Wed, 5 Nov 2014 07:16:35 +0000 (UTC) Received: (qmail 35455 invoked by uid 500); 5 Nov 2014 07:16:34 -0000 Delivered-To: apmail-hive-dev-archive@hive.apache.org Received: (qmail 35359 invoked by uid 500); 5 Nov 2014 07:16:34 -0000 Mailing-List: contact dev-help@hive.apache.org; run by ezmlm Precedence: bulk List-Help: List-Unsubscribe: List-Post: List-Id: Reply-To: dev@hive.apache.org Delivered-To: mailing list dev@hive.apache.org Received: (qmail 35128 invoked by uid 500); 5 Nov 2014 07:16:34 -0000 Delivered-To: apmail-hadoop-hive-dev@hadoop.apache.org Received: (qmail 35066 invoked by uid 99); 5 Nov 2014 07:16:34 -0000 Received: from arcas.apache.org (HELO arcas.apache.org) (140.211.11.28) by apache.org (qpsmtpd/0.29) with ESMTP; Wed, 05 Nov 2014 07:16:34 +0000 Date: Wed, 5 Nov 2014 07:16:34 +0000 (UTC) From: "Gunther Hagleitner (JIRA)" To: hive-dev@hadoop.apache.org Message-ID: In-Reply-To: References: Subject: [jira] [Updated] (HIVE-8731) TPC-DS Q49 : Semantic analyzer order by is not honored when used after union all MIME-Version: 1.0 Content-Type: text/plain; charset=utf-8 Content-Transfer-Encoding: 7bit X-JIRA-FingerPrint: 30527f35849b9dde25b450d4833f0394 [ https://issues.apache.org/jira/browse/HIVE-8731?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Gunther Hagleitner updated HIVE-8731: ------------------------------------- Fix Version/s: (was: 0.14.0) > TPC-DS Q49 : Semantic analyzer order by is not honored when used after union all > --------------------------------------------------------------------------------- > > Key: HIVE-8731 > URL: https://issues.apache.org/jira/browse/HIVE-8731 > Project: Hive > Issue Type: Bug > Components: Vectorization > Affects Versions: 0.13.0, 0.14.0 > Reporter: Mostafa Mokhtar > Assignee: Gunther Hagleitner > Priority: Critical > > TPC-DS query 49 returns more rows than that set in limit. > Query > {code} > set hive.cbo.enable=true; > set hive.stats.fetch.column.stats=true; > set hive.exec.dynamic.partition.mode=nonstrict; > set hive.tez.auto.reducer.parallelism=true; > set hive.auto.convert.join.noconditionaltask.size=1280000000; > set hive.exec.reducers.bytes.per.reducer=100000000; > set hive.txn.manager=org.apache.hadoop.hive.ql.lockmgr.DummyTxnManager; > set hive.support.concurrency=false; > set hive.tez.exec.print.summary=true; > explain > select > 'web' as channel > ,web.item > ,web.return_ratio > ,web.return_rank > ,web.currency_rank > from ( > select > item > ,return_ratio > ,currency_ratio > ,rank() over (order by return_ratio) as return_rank > ,rank() over (order by currency_ratio) as currency_rank > from > ( select ws.ws_item_sk as item > ,(cast(sum(coalesce(wr.wr_return_quantity,0)) as decimal(15,4))/ > cast(sum(coalesce(ws.ws_quantity,0)) as decimal(15,4) )) as return_ratio > ,(cast(sum(coalesce(wr.wr_return_amt,0)) as decimal(15,4))/ > cast(sum(coalesce(ws.ws_net_paid,0)) as decimal(15,4) )) as currency_ratio > from > web_sales ws left outer join web_returns wr > on (ws.ws_order_number = wr.wr_order_number and > ws.ws_item_sk = wr.wr_item_sk) > ,date_dim > where > wr.wr_return_amt > 10000 > and ws.ws_net_profit > 1 > and ws.ws_net_paid > 0 > and ws.ws_quantity > 0 > and ws.ws_sold_date_sk = date_dim.d_date_sk > and d_year = 2000 > and d_moy = 12 > group by ws.ws_item_sk > ) in_web > ) web > where > ( > web.return_rank <= 10 > or > web.currency_rank <= 10 > ) > union all > select > 'catalog' as channel > ,catalog.item > ,catalog.return_ratio > ,catalog.return_rank > ,catalog.currency_rank > from ( > select > item > ,return_ratio > ,currency_ratio > ,rank() over (order by return_ratio) as return_rank > ,rank() over (order by currency_ratio) as currency_rank > from > ( select > cs.cs_item_sk as item > ,(cast(sum(coalesce(cr.cr_return_quantity,0)) as decimal(15,4))/ > cast(sum(coalesce(cs.cs_quantity,0)) as decimal(15,4) )) as return_ratio > ,(cast(sum(coalesce(cr.cr_return_amount,0)) as decimal(15,4))/ > cast(sum(coalesce(cs.cs_net_paid,0)) as decimal(15,4) )) as currency_ratio > from > catalog_sales cs left outer join catalog_returns cr > on (cs.cs_order_number = cr.cr_order_number and > cs.cs_item_sk = cr.cr_item_sk) > ,date_dim > where > cr.cr_return_amount > 10000 > and cs.cs_net_profit > 1 > and cs.cs_net_paid > 0 > and cs.cs_quantity > 0 > and cs_sold_date_sk = d_date_sk > and d_year = 2000 > and d_moy = 12 > group by cs.cs_item_sk > ) in_cat > ) catalog > where > ( > catalog.return_rank <= 10 > or > catalog.currency_rank <=10 > ) > union all > select > 'store' as channel > ,store.item > ,store.return_ratio > ,store.return_rank > ,store.currency_rank > from ( > select > item > ,return_ratio > ,currency_ratio > ,rank() over (order by return_ratio) as return_rank > ,rank() over (order by currency_ratio) as currency_rank > from > ( select sts.ss_item_sk as item > ,(cast(sum(coalesce(sr.sr_return_quantity,0)) as decimal(15,4))/cast(sum(coalesce(sts.ss_quantity,0)) as decimal(15,4) )) as return_ratio > ,(cast(sum(coalesce(sr.sr_return_amt,0)) as decimal(15,4))/cast(sum(coalesce(sts.ss_net_paid,0)) as decimal(15,4) )) as currency_ratio > from > store_sales sts left outer join store_returns sr > on (sts.ss_ticket_number = sr.sr_ticket_number and sts.ss_item_sk = sr.sr_item_sk) > ,date_dim > where > sr.sr_return_amt > 10000 > and sts.ss_net_profit > 1 > and sts.ss_net_paid > 0 > and sts.ss_quantity > 0 > and ss_sold_date_sk = d_date_sk > and d_year = 2000 > and d_moy = 12 > group by sts.ss_item_sk > ) in_store > ) store > where ( > store.return_rank <= 10 > or > store.currency_rank <= 10 > ) > order by 1,4,5 > limit 100 > {code} > Explain > {code} > OK > STAGE DEPENDENCIES: > Stage-1 is a root stage > Stage-0 depends on stages: Stage-1 > STAGE PLANS: > Stage: Stage-1 > Tez > Edges: > Map 11 <- Map 2 (BROADCAST_EDGE) > Map 16 <- Map 1 (BROADCAST_EDGE) > Map 9 <- Map 10 (BROADCAST_EDGE) > Reducer 12 <- Map 11 (SIMPLE_EDGE), Map 23 (SIMPLE_EDGE) > Reducer 13 <- Reducer 12 (SIMPLE_EDGE) > Reducer 14 <- Reducer 13 (SIMPLE_EDGE) > Reducer 15 <- Reducer 14 (SIMPLE_EDGE), Union 8 (CONTAINS) > Reducer 17 <- Map 16 (SIMPLE_EDGE), Map 22 (SIMPLE_EDGE) > Reducer 18 <- Reducer 17 (SIMPLE_EDGE) > Reducer 19 <- Reducer 18 (SIMPLE_EDGE) > Reducer 20 <- Reducer 19 (SIMPLE_EDGE) > Reducer 21 <- Reducer 20 (SIMPLE_EDGE), Union 8 (CONTAINS) > Reducer 4 <- Map 3 (SIMPLE_EDGE), Map 9 (SIMPLE_EDGE) > Reducer 5 <- Reducer 4 (SIMPLE_EDGE) > Reducer 6 <- Reducer 5 (SIMPLE_EDGE) > Reducer 7 <- Reducer 6 (SIMPLE_EDGE), Union 8 (CONTAINS) > DagName: mmokhtar_20141104031616_2feed955-8bb2-41e9-a7be-247a5fd102f0:1 > Vertices: > Map 1 > Map Operator Tree: > TableScan > alias: date_dim > filterExpr: (((d_year = 2000) and (d_moy = 12)) and d_date_sk is not null) (type: boolean) > Statistics: Num rows: 73049 Data size: 81741831 Basic stats: COMPLETE Column stats: COMPLETE > Filter Operator > predicate: (((d_year = 2000) and (d_moy = 12)) and d_date_sk is not null) (type: boolean) > Statistics: Num rows: 652 Data size: 7824 Basic stats: COMPLETE Column stats: COMPLETE > Select Operator > expressions: d_date_sk (type: int) > outputColumnNames: _col0 > Statistics: Num rows: 652 Data size: 2608 Basic stats: COMPLETE Column stats: COMPLETE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 652 Data size: 2608 Basic stats: COMPLETE Column stats: COMPLETE > Select Operator > expressions: _col0 (type: int) > outputColumnNames: _col0 > Statistics: Num rows: 652 Data size: 2608 Basic stats: COMPLETE Column stats: COMPLETE > Group By Operator > keys: _col0 (type: int) > mode: hash > outputColumnNames: _col0 > Statistics: Num rows: 326 Data size: 1304 Basic stats: COMPLETE Column stats: COMPLETE > Dynamic Partitioning Event Operator > Target Input: sts > Partition key expr: ss_sold_date_sk > Statistics: Num rows: 326 Data size: 1304 Basic stats: COMPLETE Column stats: COMPLETE > Target column: ss_sold_date_sk > Target Vertex: Map 16 > Execution mode: vectorized > Map 10 > Map Operator Tree: > TableScan > alias: date_dim > filterExpr: (((d_year = 2000) and (d_moy = 12)) and d_date_sk is not null) (type: boolean) > Statistics: Num rows: 73049 Data size: 81741831 Basic stats: COMPLETE Column stats: COMPLETE > Filter Operator > predicate: (((d_year = 2000) and (d_moy = 12)) and d_date_sk is not null) (type: boolean) > Statistics: Num rows: 652 Data size: 7824 Basic stats: COMPLETE Column stats: COMPLETE > Select Operator > expressions: d_date_sk (type: int) > outputColumnNames: _col0 > Statistics: Num rows: 652 Data size: 2608 Basic stats: COMPLETE Column stats: COMPLETE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 652 Data size: 2608 Basic stats: COMPLETE Column stats: COMPLETE > Select Operator > expressions: _col0 (type: int) > outputColumnNames: _col0 > Statistics: Num rows: 652 Data size: 2608 Basic stats: COMPLETE Column stats: COMPLETE > Group By Operator > keys: _col0 (type: int) > mode: hash > outputColumnNames: _col0 > Statistics: Num rows: 326 Data size: 1304 Basic stats: COMPLETE Column stats: COMPLETE > Dynamic Partitioning Event Operator > Target Input: ws > Partition key expr: ws_sold_date_sk > Statistics: Num rows: 326 Data size: 1304 Basic stats: COMPLETE Column stats: COMPLETE > Target column: ws_sold_date_sk > Target Vertex: Map 9 > Execution mode: vectorized > Map 11 > Map Operator Tree: > TableScan > alias: cs > filterExpr: (((((cs_net_profit > 1.0) and (cs_net_paid > 0.0)) and (cs_quantity > 0)) and cs_order_number is not null) and cs_item_sk is not null) (type: boolean) > Statistics: Num rows: 43005109025 Data size: 5569553841288 Basic stats: COMPLETE Column stats: COMPLETE > Filter Operator > predicate: (((((cs_net_profit > 1.0) and (cs_net_paid > 0.0)) and (cs_quantity > 0)) and cs_order_number is not null) and cs_item_sk is not null) (type: boolean) > Statistics: Num rows: 712248037 Data size: 15504677212 Basic stats: COMPLETE Column stats: COMPLETE > Select Operator > expressions: cs_item_sk (type: int), cs_order_number (type: int), cs_quantity (type: int), cs_net_paid (type: float), cs_sold_date_sk (type: int) > outputColumnNames: _col0, _col1, _col2, _col3, _col5 > Statistics: Num rows: 712248037 Data size: 12655685064 Basic stats: COMPLETE Column stats: COMPLETE > Map Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0 {_col0} {_col1} {_col2} {_col3} > 1 > keys: > 0 _col5 (type: int) > 1 _col0 (type: int) > outputColumnNames: _col0, _col1, _col2, _col3 > input vertices: > 1 Map 2 > Statistics: Num rows: 795181027 Data size: 12722896432 Basic stats: COMPLETE Column stats: COMPLETE > Select Operator > expressions: _col0 (type: int), _col1 (type: int), _col2 (type: int), _col3 (type: float) > outputColumnNames: _col0, _col1, _col2, _col3 > Statistics: Num rows: 795181027 Data size: 12722896432 Basic stats: COMPLETE Column stats: COMPLETE > Reduce Output Operator > key expressions: _col1 (type: int), _col0 (type: int) > sort order: ++ > Map-reduce partition columns: _col1 (type: int), _col0 (type: int) > Statistics: Num rows: 795181027 Data size: 12722896432 Basic stats: COMPLETE Column stats: COMPLETE > value expressions: _col2 (type: int), _col3 (type: float) > Execution mode: vectorized > Map 16 > Map Operator Tree: > TableScan > alias: sts > filterExpr: (((((ss_net_profit > 1.0) and (ss_net_paid > 0.0)) and (ss_quantity > 0)) and ss_ticket_number is not null) and ss_item_sk is not null) (type: boolean) > Statistics: Num rows: 82510879939 Data size: 6873789738208 Basic stats: COMPLETE Column stats: COMPLETE > Filter Operator > predicate: (((((ss_net_profit > 1.0) and (ss_net_paid > 0.0)) and (ss_quantity > 0)) and ss_ticket_number is not null) and ss_item_sk is not null) (type: boolean) > Statistics: Num rows: 911486684 Data size: 19059525624 Basic stats: COMPLETE Column stats: COMPLETE > Select Operator > expressions: ss_item_sk (type: int), ss_ticket_number (type: int), ss_quantity (type: int), ss_net_paid (type: float), ss_sold_date_sk (type: int) > outputColumnNames: _col0, _col1, _col2, _col3, _col5 > Statistics: Num rows: 911486684 Data size: 15499570644 Basic stats: COMPLETE Column stats: COMPLETE > Map Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0 {_col0} {_col1} {_col2} {_col3} > 1 > keys: > 0 _col5 (type: int) > 1 _col0 (type: int) > outputColumnNames: _col0, _col1, _col2, _col3 > input vertices: > 1 Map 1 > Statistics: Num rows: 1017618695 Data size: 16281899120 Basic stats: COMPLETE Column stats: COMPLETE > Select Operator > expressions: _col0 (type: int), _col1 (type: int), _col2 (type: int), _col3 (type: float) > outputColumnNames: _col0, _col1, _col2, _col3 > Statistics: Num rows: 1017618695 Data size: 16281899120 Basic stats: COMPLETE Column stats: COMPLETE > Reduce Output Operator > key expressions: _col1 (type: int), _col0 (type: int) > sort order: ++ > Map-reduce partition columns: _col1 (type: int), _col0 (type: int) > Statistics: Num rows: 1017618695 Data size: 16281899120 Basic stats: COMPLETE Column stats: COMPLETE > value expressions: _col2 (type: int), _col3 (type: float) > Execution mode: vectorized > Map 2 > Map Operator Tree: > TableScan > alias: date_dim > filterExpr: (((d_year = 2000) and (d_moy = 12)) and d_date_sk is not null) (type: boolean) > Statistics: Num rows: 73049 Data size: 81741831 Basic stats: COMPLETE Column stats: COMPLETE > Filter Operator > predicate: (((d_year = 2000) and (d_moy = 12)) and d_date_sk is not null) (type: boolean) > Statistics: Num rows: 652 Data size: 7824 Basic stats: COMPLETE Column stats: COMPLETE > Select Operator > expressions: d_date_sk (type: int) > outputColumnNames: _col0 > Statistics: Num rows: 652 Data size: 2608 Basic stats: COMPLETE Column stats: COMPLETE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 652 Data size: 2608 Basic stats: COMPLETE Column stats: COMPLETE > Select Operator > expressions: _col0 (type: int) > outputColumnNames: _col0 > Statistics: Num rows: 652 Data size: 2608 Basic stats: COMPLETE Column stats: COMPLETE > Group By Operator > keys: _col0 (type: int) > mode: hash > outputColumnNames: _col0 > Statistics: Num rows: 326 Data size: 1304 Basic stats: COMPLETE Column stats: COMPLETE > Dynamic Partitioning Event Operator > Target Input: cs > Partition key expr: cs_sold_date_sk > Statistics: Num rows: 326 Data size: 1304 Basic stats: COMPLETE Column stats: COMPLETE > Target column: cs_sold_date_sk > Target Vertex: Map 11 > Execution mode: vectorized > Map 22 > Map Operator Tree: > TableScan > alias: sr > filterExpr: (((sr_return_amt > 10000.0) and sr_ticket_number is not null) and sr_item_sk is not null) (type: boolean) > Statistics: Num rows: 8332595709 Data size: 599630285540 Basic stats: COMPLETE Column stats: COMPLETE > Filter Operator > predicate: (((sr_return_amt > 10000.0) and sr_ticket_number is not null) and sr_item_sk is not null) (type: boolean) > Statistics: Num rows: 828937940 Data size: 10816321020 Basic stats: COMPLETE Column stats: COMPLETE > Select Operator > expressions: sr_item_sk (type: int), sr_ticket_number (type: int), sr_return_quantity (type: int), sr_return_amt (type: float) > outputColumnNames: _col0, _col1, _col2, _col3 > Statistics: Num rows: 828937940 Data size: 10816321020 Basic stats: COMPLETE Column stats: COMPLETE > Reduce Output Operator > key expressions: _col1 (type: int), _col0 (type: int) > sort order: ++ > Map-reduce partition columns: _col1 (type: int), _col0 (type: int) > Statistics: Num rows: 828937940 Data size: 10816321020 Basic stats: COMPLETE Column stats: COMPLETE > value expressions: _col2 (type: int), _col3 (type: float) > Execution mode: vectorized > Map 23 > Map Operator Tree: > TableScan > alias: cr > filterExpr: (((cr_return_amount > 10000.0) and cr_order_number is not null) and cr_item_sk is not null) (type: boolean) > Statistics: Num rows: 4320980099 Data size: 431907559456 Basic stats: COMPLETE Column stats: COMPLETE > Filter Operator > predicate: (((cr_return_amount > 10000.0) and cr_order_number is not null) and cr_item_sk is not null) (type: boolean) > Statistics: Num rows: 644267320 Data size: 8780816984 Basic stats: COMPLETE Column stats: COMPLETE > Select Operator > expressions: cr_item_sk (type: int), cr_order_number (type: int), cr_return_quantity (type: int), cr_return_amount (type: float) > outputColumnNames: _col0, _col1, _col2, _col3 > Statistics: Num rows: 644267320 Data size: 8780816984 Basic stats: COMPLETE Column stats: COMPLETE > Reduce Output Operator > key expressions: _col1 (type: int), _col0 (type: int) > sort order: ++ > Map-reduce partition columns: _col1 (type: int), _col0 (type: int) > Statistics: Num rows: 644267320 Data size: 8780816984 Basic stats: COMPLETE Column stats: COMPLETE > value expressions: _col2 (type: int), _col3 (type: float) > Execution mode: vectorized > Map 3 > Map Operator Tree: > TableScan > alias: wr > filterExpr: (((wr_return_amt > 10000.0) and wr_order_number is not null) and wr_item_sk is not null) (type: boolean) > Statistics: Num rows: 2062802370 Data size: 185695406284 Basic stats: COMPLETE Column stats: COMPLETE > Filter Operator > predicate: (((wr_return_amt > 10000.0) and wr_order_number is not null) and wr_item_sk is not null) (type: boolean) > Statistics: Num rows: 687600790 Data size: 10872009264 Basic stats: COMPLETE Column stats: COMPLETE > Select Operator > expressions: wr_item_sk (type: int), wr_order_number (type: int), wr_return_quantity (type: int), wr_return_amt (type: float) > outputColumnNames: _col0, _col1, _col2, _col3 > Statistics: Num rows: 687600790 Data size: 10872009264 Basic stats: COMPLETE Column stats: COMPLETE > Reduce Output Operator > key expressions: _col1 (type: int), _col0 (type: int) > sort order: ++ > Map-reduce partition columns: _col1 (type: int), _col0 (type: int) > Statistics: Num rows: 687600790 Data size: 10872009264 Basic stats: COMPLETE Column stats: COMPLETE > value expressions: _col2 (type: int), _col3 (type: float) > Execution mode: vectorized > Map 9 > Map Operator Tree: > TableScan > alias: ws > filterExpr: (((((ws_net_profit > 1.0) and (ws_net_paid > 0.0)) and (ws_quantity > 0)) and ws_order_number is not null) and ws_item_sk is not null) (type: boolean) > Statistics: Num rows: 21594638446 Data size: 2850189889652 Basic stats: COMPLETE Column stats: COMPLETE > Filter Operator > predicate: (((((ws_net_profit > 1.0) and (ws_net_paid > 0.0)) and (ws_quantity > 0)) and ws_order_number is not null) and ws_item_sk is not null) (type: boolean) > Statistics: Num rows: 799801423 Data size: 19194435896 Basic stats: COMPLETE Column stats: COMPLETE > Select Operator > expressions: ws_item_sk (type: int), ws_order_number (type: int), ws_quantity (type: int), ws_net_paid (type: float), ws_sold_date_sk (type: int) > outputColumnNames: _col0, _col1, _col2, _col3, _col5 > Statistics: Num rows: 799801423 Data size: 15995230204 Basic stats: COMPLETE Column stats: COMPLETE > Map Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0 {_col0} {_col1} {_col2} {_col3} > 1 > keys: > 0 _col5 (type: int) > 1 _col0 (type: int) > outputColumnNames: _col0, _col1, _col2, _col3 > input vertices: > 1 Map 10 > Statistics: Num rows: 892928985 Data size: 14286863760 Basic stats: COMPLETE Column stats: COMPLETE > Select Operator > expressions: _col0 (type: int), _col1 (type: int), _col2 (type: int), _col3 (type: float) > outputColumnNames: _col0, _col1, _col2, _col3 > Statistics: Num rows: 892928985 Data size: 14286863760 Basic stats: COMPLETE Column stats: COMPLETE > Reduce Output Operator > key expressions: _col1 (type: int), _col0 (type: int) > sort order: ++ > Map-reduce partition columns: _col1 (type: int), _col0 (type: int) > Statistics: Num rows: 892928985 Data size: 14286863760 Basic stats: COMPLETE Column stats: COMPLETE > value expressions: _col2 (type: int), _col3 (type: float) > Execution mode: vectorized > Reducer 12 > Reduce Operator Tree: > Merge Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0 {VALUE._col0} {VALUE._col1} > 1 {KEY.reducesinkkey1} {VALUE._col0} {VALUE._col1} > outputColumnNames: _col2, _col3, _col4, _col6, _col7 > Statistics: Num rows: 750469116 Data size: 9005629392 Basic stats: COMPLETE Column stats: COMPLETE > Select Operator > expressions: _col4 (type: int), COALESCE(_col2,0) (type: int), COALESCE(_col6,0) (type: int), COALESCE(_col3,0) (type: float), COALESCE(_col7,0) (type: float) > outputColumnNames: _col0, _col1, _col2, _col3, _col4 > Statistics: Num rows: 750469116 Data size: 9005629392 Basic stats: COMPLETE Column stats: COMPLETE > Group By Operator > aggregations: sum(_col1), sum(_col2), sum(_col3), sum(_col4) > keys: _col0 (type: int) > mode: hash > outputColumnNames: _col0, _col1, _col2, _col3, _col4 > Statistics: Num rows: 461643 Data size: 16619148 Basic stats: COMPLETE Column stats: COMPLETE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 461643 Data size: 16619148 Basic stats: COMPLETE Column stats: COMPLETE > value expressions: _col1 (type: bigint), _col2 (type: bigint), _col3 (type: double), _col4 (type: double) > Reducer 13 > Reduce Operator Tree: > Group By Operator > aggregations: sum(VALUE._col0), sum(VALUE._col1), sum(VALUE._col2), sum(VALUE._col3) > keys: KEY._col0 (type: int) > mode: mergepartial > outputColumnNames: _col0, _col1, _col2, _col3, _col4 > Statistics: Num rows: 5073 Data size: 182628 Basic stats: COMPLETE Column stats: COMPLETE > Select Operator > expressions: _col0 (type: int), (CAST( _col1 AS decimal(15,4)) / CAST( _col2 AS decimal(15,4))) (type: decimal(35,20)), (CAST( _col3 AS decimal(15,4)) / CAST( _col4 AS decimal(15,4))) (type: decimal(35,20)) > outputColumnNames: _col0, _col1, _col2 > Statistics: Num rows: 5073 Data size: 1156644 Basic stats: COMPLETE Column stats: COMPLETE > Reduce Output Operator > key expressions: 0 (type: int), _col1 (type: decimal(35,20)) > sort order: ++ > Map-reduce partition columns: 0 (type: int) > Statistics: Num rows: 5073 Data size: 1156644 Basic stats: COMPLETE Column stats: COMPLETE > value expressions: _col0 (type: int), _col1 (type: decimal(35,20)), _col2 (type: decimal(35,20)) > Execution mode: vectorized > Reducer 14 > Reduce Operator Tree: > Extract > Statistics: Num rows: 5073 Data size: 1156644 Basic stats: COMPLETE Column stats: COMPLETE > PTF Operator > Statistics: Num rows: 5073 Data size: 1156644 Basic stats: COMPLETE Column stats: COMPLETE > Reduce Output Operator > key expressions: 0 (type: int), _col2 (type: decimal(35,20)) > sort order: ++ > Map-reduce partition columns: 0 (type: int) > Statistics: Num rows: 5073 Data size: 1156644 Basic stats: COMPLETE Column stats: COMPLETE > value expressions: _wcol0 (type: int), _col0 (type: int), _col1 (type: decimal(35,20)), _col2 (type: decimal(35,20)) > Reducer 15 > Reduce Operator Tree: > Extract > PTF Operator > Filter Operator > predicate: ((_col0 <= 10) or (_wcol1 <= 10)) (type: boolean) > Select Operator > expressions: 'catalog' (type: string), _col1 (type: int), _col2 (type: decimal(35,20)), _col0 (type: int), _wcol1 (type: int) > outputColumnNames: _col0, _col1, _col2, _col3, _col4 > Select Operator > expressions: _col0 (type: string), _col1 (type: int), _col2 (type: decimal(35,20)), _col3 (type: int), _col4 (type: int) > outputColumnNames: _col0, _col1, _col2, _col3, _col4 > File Output Operator > compressed: false > table: > input format: org.apache.hadoop.mapred.TextInputFormat > output format: org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat > serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe > Reducer 17 > Reduce Operator Tree: > Merge Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0 {VALUE._col0} {VALUE._col1} > 1 {KEY.reducesinkkey1} {VALUE._col0} {VALUE._col1} > outputColumnNames: _col2, _col3, _col4, _col6, _col7 > Statistics: Num rows: 5092708834 Data size: 61112506008 Basic stats: COMPLETE Column stats: COMPLETE > Select Operator > expressions: _col4 (type: int), COALESCE(_col2,0) (type: int), COALESCE(_col6,0) (type: int), COALESCE(_col3,0) (type: float), COALESCE(_col7,0) (type: float) > outputColumnNames: _col0, _col1, _col2, _col3, _col4 > Statistics: Num rows: 5092708834 Data size: 61112506008 Basic stats: COMPLETE Column stats: COMPLETE > Group By Operator > aggregations: sum(_col1), sum(_col2), sum(_col3), sum(_col4) > keys: _col0 (type: int) > mode: hash > outputColumnNames: _col0, _col1, _col2, _col3, _col4 > Statistics: Num rows: 2194632 Data size: 79006752 Basic stats: COMPLETE Column stats: COMPLETE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 2194632 Data size: 79006752 Basic stats: COMPLETE Column stats: COMPLETE > value expressions: _col1 (type: bigint), _col2 (type: bigint), _col3 (type: double), _col4 (type: double) > Reducer 18 > Reduce Operator Tree: > Group By Operator > aggregations: sum(VALUE._col0), sum(VALUE._col1), sum(VALUE._col2), sum(VALUE._col3) > keys: KEY._col0 (type: int) > mode: mergepartial > outputColumnNames: _col0, _col1, _col2, _col3, _col4 > Statistics: Num rows: 3586 Data size: 129096 Basic stats: COMPLETE Column stats: COMPLETE > Select Operator > expressions: _col0 (type: int), (CAST( _col1 AS decimal(15,4)) / CAST( _col2 AS decimal(15,4))) (type: decimal(35,20)), (CAST( _col3 AS decimal(15,4)) / CAST( _col4 AS decimal(15,4))) (type: decimal(35,20)) > outputColumnNames: _col0, _col1, _col2 > Statistics: Num rows: 3586 Data size: 817608 Basic stats: COMPLETE Column stats: COMPLETE > Reduce Output Operator > key expressions: 0 (type: int), _col1 (type: decimal(35,20)) > sort order: ++ > Map-reduce partition columns: 0 (type: int) > Statistics: Num rows: 3586 Data size: 817608 Basic stats: COMPLETE Column stats: COMPLETE > value expressions: _col0 (type: int), _col1 (type: decimal(35,20)), _col2 (type: decimal(35,20)) > Execution mode: vectorized > Reducer 19 > Reduce Operator Tree: > Extract > Statistics: Num rows: 3586 Data size: 817608 Basic stats: COMPLETE Column stats: COMPLETE > PTF Operator > Statistics: Num rows: 3586 Data size: 817608 Basic stats: COMPLETE Column stats: COMPLETE > Reduce Output Operator > key expressions: 0 (type: int), _col2 (type: decimal(35,20)) > sort order: ++ > Map-reduce partition columns: 0 (type: int) > Statistics: Num rows: 3586 Data size: 817608 Basic stats: COMPLETE Column stats: COMPLETE > value expressions: _wcol0 (type: int), _col0 (type: int), _col1 (type: decimal(35,20)), _col2 (type: decimal(35,20)) > Reducer 20 > Reduce Operator Tree: > Extract > Statistics: Num rows: 3586 Data size: 817608 Basic stats: COMPLETE Column stats: COMPLETE > PTF Operator > Statistics: Num rows: 3586 Data size: 817608 Basic stats: COMPLETE Column stats: COMPLETE > Filter Operator > predicate: ((_col0 <= 10) or (_wcol1 <= 10)) (type: boolean) > Statistics: Num rows: 2390 Data size: 0 Basic stats: PARTIAL Column stats: COMPLETE > Select Operator > expressions: 'store' (type: string), _col1 (type: int), _col2 (type: decimal(35,20)), _col0 (type: int), _wcol1 (type: int), 1 (type: int), 4 (type: int), 5 (type: int) > outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7 > Statistics: Num rows: 2390 Data size: 0 Basic stats: PARTIAL Column stats: COMPLETE > Reduce Output Operator > key expressions: _col5 (type: int), _col6 (type: int), _col7 (type: int) > sort order: +++ > Statistics: Num rows: 2390 Data size: 0 Basic stats: PARTIAL Column stats: COMPLETE > TopN Hash Memory Usage: 0.04 > value expressions: _col0 (type: string), _col1 (type: int), _col2 (type: decimal(35,20)), _col3 (type: int), _col4 (type: int) > Reducer 21 > Reduce Operator Tree: > Select Operator > expressions: VALUE._col0 (type: string), VALUE._col1 (type: int), VALUE._col2 (type: decimal(35,20)), VALUE._col3 (type: int), VALUE._col4 (type: int) > outputColumnNames: _col0, _col1, _col2, _col3, _col4 > Limit > Number of rows: 100 > Select Operator > expressions: _col0 (type: string), _col1 (type: int), _col2 (type: decimal(35,20)), _col3 (type: int), _col4 (type: int) > outputColumnNames: _col0, _col1, _col2, _col3, _col4 > Select Operator > expressions: _col0 (type: string), _col1 (type: int), _col2 (type: decimal(35,20)), _col3 (type: int), _col4 (type: int) > outputColumnNames: _col0, _col1, _col2, _col3, _col4 > File Output Operator > compressed: false > table: > input format: org.apache.hadoop.mapred.TextInputFormat > output format: org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat > serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe > Execution mode: vectorized > Reducer 4 > Reduce Operator Tree: > Merge Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0 {VALUE._col0} {VALUE._col1} > 1 {KEY.reducesinkkey1} {VALUE._col0} {VALUE._col1} > outputColumnNames: _col2, _col3, _col4, _col6, _col7 > Statistics: Num rows: 375616827 Data size: 4507401924 Basic stats: COMPLETE Column stats: COMPLETE > Select Operator > expressions: _col4 (type: int), COALESCE(_col2,0) (type: int), COALESCE(_col6,0) (type: int), COALESCE(_col3,0) (type: float), COALESCE(_col7,0) (type: float) > outputColumnNames: _col0, _col1, _col2, _col3, _col4 > Statistics: Num rows: 375616827 Data size: 4507401924 Basic stats: COMPLETE Column stats: COMPLETE > Group By Operator > aggregations: sum(_col1), sum(_col2), sum(_col3), sum(_col4) > keys: _col0 (type: int) > mode: hash > outputColumnNames: _col0, _col1, _col2, _col3, _col4 > Statistics: Num rows: 232622 Data size: 8374392 Basic stats: COMPLETE Column stats: COMPLETE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 232622 Data size: 8374392 Basic stats: COMPLETE Column stats: COMPLETE > value expressions: _col1 (type: bigint), _col2 (type: bigint), _col3 (type: double), _col4 (type: double) > Reducer 5 > Reduce Operator Tree: > Group By Operator > aggregations: sum(VALUE._col0), sum(VALUE._col1), sum(VALUE._col2), sum(VALUE._col3) > keys: KEY._col0 (type: int) > mode: mergepartial > outputColumnNames: _col0, _col1, _col2, _col3, _col4 > Statistics: Num rows: 5057 Data size: 182052 Basic stats: COMPLETE Column stats: COMPLETE > Select Operator > expressions: _col0 (type: int), (CAST( _col1 AS decimal(15,4)) / CAST( _col2 AS decimal(15,4))) (type: decimal(35,20)), (CAST( _col3 AS decimal(15,4)) / CAST( _col4 AS decimal(15,4))) (type: decimal(35,20)) > outputColumnNames: _col0, _col1, _col2 > Statistics: Num rows: 5057 Data size: 1152996 Basic stats: COMPLETE Column stats: COMPLETE > Reduce Output Operator > key expressions: 0 (type: int), _col1 (type: decimal(35,20)) > sort order: ++ > Map-reduce partition columns: 0 (type: int) > Statistics: Num rows: 5057 Data size: 1152996 Basic stats: COMPLETE Column stats: COMPLETE > value expressions: _col0 (type: int), _col1 (type: decimal(35,20)), _col2 (type: decimal(35,20)) > Execution mode: vectorized > Reducer 6 > Reduce Operator Tree: > Extract > Statistics: Num rows: 5057 Data size: 1152996 Basic stats: COMPLETE Column stats: COMPLETE > PTF Operator > Statistics: Num rows: 5057 Data size: 1152996 Basic stats: COMPLETE Column stats: COMPLETE > Reduce Output Operator > key expressions: 0 (type: int), _col2 (type: decimal(35,20)) > sort order: ++ > Map-reduce partition columns: 0 (type: int) > Statistics: Num rows: 5057 Data size: 1152996 Basic stats: COMPLETE Column stats: COMPLETE > value expressions: _wcol0 (type: int), _col0 (type: int), _col1 (type: decimal(35,20)), _col2 (type: decimal(35,20)) > Reducer 7 > Reduce Operator Tree: > Extract > PTF Operator > Filter Operator > predicate: ((_col0 <= 10) or (_wcol1 <= 10)) (type: boolean) > Select Operator > expressions: 'web' (type: string), _col1 (type: int), _col2 (type: decimal(35,20)), _col0 (type: int), _wcol1 (type: int) > outputColumnNames: _col0, _col1, _col2, _col3, _col4 > Select Operator > expressions: _col0 (type: string), _col1 (type: int), _col2 (type: decimal(35,20)), _col3 (type: int), _col4 (type: int) > outputColumnNames: _col0, _col1, _col2, _col3, _col4 > File Output Operator > compressed: false > table: > input format: org.apache.hadoop.mapred.TextInputFormat > output format: org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat > serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe > Union 8 > Vertex: Union 8 > Stage: Stage-0 > Fetch Operator > limit: -1 > Processor Tree: > ListSink > {code} > Results > {code} > OK > web 55255 0.37373737373737373737 1072 1 > web 305651 0.38383838383838383838 1138 2 > web 336757 0.38461538461538461538 1142 3 > web 256885 0.39 1191 4 > web 229082 0.39175257731958762887 1204 5 > web 151723 0.4 1265 6 > web 293861 0.4 1265 6 > web 178178 0.4 1265 8 > web 354485 0.40449438202247191011 1315 9 > web 124375 0.40625 1334 10 > web 80125 0 1 44 > web 417227 0 1 103 > web 316352 0 1 142 > web 116672 0 1 143 > web 267277 0 1 181 > web 100247 0 1 237 > web 247022 0 1 505 > web 247679 0 1 966 > web 89753 0 1 1081 > web 88964 0 1 1492 > web 292469 0 1 1771 > web 31958 0 1 1868 > web 200161 0 1 1937 > web 194660 0 1 2064 > web 381619 0 1 2233 > web 244238 0 1 2437 > web 54247 0 1 2647 > web 105464 0 1 2669 > web 297959 0 1 3196 > 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