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Posted to issues@hive.apache.org by "Mostafa Mokhtar (JIRA)" <ji...@apache.org> on 2015/04/03 00:11:53 UTC
[jira] [Resolved] (HIVE-9623) NullPointerException in
MapJoinOperator.processOp(MapJoinOperator.java:253) for TPC-DS Q75 against
un-partitioned schema
[ https://issues.apache.org/jira/browse/HIVE-9623?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Mostafa Mokhtar resolved HIVE-9623.
-----------------------------------
Resolution: Fixed
> NullPointerException in MapJoinOperator.processOp(MapJoinOperator.java:253) for TPC-DS Q75 against un-partitioned schema
> ------------------------------------------------------------------------------------------------------------------------
>
> Key: HIVE-9623
> URL: https://issues.apache.org/jira/browse/HIVE-9623
> Project: Hive
> Issue Type: Bug
> Components: Query Processor
> Affects Versions: 0.14.0
> Reporter: Mostafa Mokhtar
> Assignee: Gunther Hagleitner
> Fix For: 1.2.0
>
>
> Running TPC-DS Q75 against a non-partitioned schema fails with
> {code}
> Caused by: org.apache.hadoop.hive.ql.metadata.HiveException: Unexpected exception: null
> at org.apache.hadoop.hive.ql.exec.MapJoinOperator.processOp(MapJoinOperator.java:314)
> at org.apache.hadoop.hive.ql.exec.Operator.forward(Operator.java:815)
> at org.apache.hadoop.hive.ql.exec.CommonJoinOperator.internalForward(CommonJoinOperator.java:638)
> at org.apache.hadoop.hive.ql.exec.CommonJoinOperator.createForwardJoinObject(CommonJoinOperator.java:433)
> at org.apache.hadoop.hive.ql.exec.CommonJoinOperator.genObject(CommonJoinOperator.java:525)
> at org.apache.hadoop.hive.ql.exec.CommonJoinOperator.genObject(CommonJoinOperator.java:522)
> at org.apache.hadoop.hive.ql.exec.CommonJoinOperator.genJoinObject(CommonJoinOperator.java:451)
> at org.apache.hadoop.hive.ql.exec.CommonJoinOperator.checkAndGenObject(CommonJoinOperator.java:752)
> at org.apache.hadoop.hive.ql.exec.CommonMergeJoinOperator.joinObject(CommonMergeJoinOperator.java:248)
> at org.apache.hadoop.hive.ql.exec.CommonMergeJoinOperator.joinOneGroup(CommonMergeJoinOperator.java:213)
> at org.apache.hadoop.hive.ql.exec.CommonMergeJoinOperator.processOp(CommonMergeJoinOperator.java:196)
> at org.apache.hadoop.hive.ql.exec.tez.ReduceRecordSource$GroupIterator.next(ReduceRecordSource.java:328)
> ... 16 more
> Caused by: java.lang.NullPointerException
> at org.apache.hadoop.hive.ql.exec.MapJoinOperator.processOp(MapJoinOperator.java:253)
> ... 27 more
> {code}
> This line maps to hashMapRowGetters = new ReusableGetAdaptor[mapJoinTables.length] in the code snippet below
> {code}
> alias = (byte) tag;
> if (hashMapRowGetters == null) {
> hashMapRowGetters = new ReusableGetAdaptor[mapJoinTables.length];
> MapJoinKey refKey = getRefKey(alias);
> for (byte pos = 0; pos < order.length; pos++) {
> if (pos != alias) {
> hashMapRowGetters[pos] = mapJoinTables[pos].createGetter(refKey);
> }
> }
> }
> {code}
> Query
> {code}
> WITH all_sales AS (
> SELECT d_year
> ,i_brand_id
> ,i_class_id
> ,i_category_id
> ,i_manufact_id
> ,SUM(sales_cnt) AS sales_cnt
> ,SUM(sales_amt) AS sales_amt
> FROM (SELECT d_year
> ,i_brand_id
> ,i_class_id
> ,i_category_id
> ,i_manufact_id
> ,cs_quantity - COALESCE(cr_return_quantity,0) AS sales_cnt
> ,cs_ext_sales_price - COALESCE(cr_return_amount,0.0) AS sales_amt
> FROM catalog_sales JOIN item ON i_item_sk=cs_item_sk
> JOIN date_dim ON d_date_sk=cs_sold_date_sk
> LEFT JOIN catalog_returns ON (cs_order_number=cr_order_number
> AND cs_item_sk=cr_item_sk)
> WHERE i_category='Sports'
> UNION ALL
> SELECT d_year
> ,i_brand_id
> ,i_class_id
> ,i_category_id
> ,i_manufact_id
> ,ss_quantity - COALESCE(sr_return_quantity,0) AS sales_cnt
> ,ss_ext_sales_price - COALESCE(sr_return_amt,0.0) AS sales_amt
> FROM store_sales JOIN item ON i_item_sk=ss_item_sk
> JOIN date_dim ON d_date_sk=ss_sold_date_sk
> LEFT JOIN store_returns ON (ss_ticket_number=sr_ticket_number
> AND ss_item_sk=sr_item_sk)
> WHERE i_category='Sports'
> UNION ALL
> SELECT d_year
> ,i_brand_id
> ,i_class_id
> ,i_category_id
> ,i_manufact_id
> ,ws_quantity - COALESCE(wr_return_quantity,0) AS sales_cnt
> ,ws_ext_sales_price - COALESCE(wr_return_amt,0.0) AS sales_amt
> FROM web_sales JOIN item ON i_item_sk=ws_item_sk
> JOIN date_dim ON d_date_sk=ws_sold_date_sk
> LEFT JOIN web_returns ON (ws_order_number=wr_order_number
> AND ws_item_sk=wr_item_sk)
> WHERE i_category='Sports') sales_detail
> GROUP BY d_year, i_brand_id, i_class_id, i_category_id, i_manufact_id)
> SELECT prev_yr.d_year AS prev_year
> ,curr_yr.d_year AS year
> ,curr_yr.i_brand_id
> ,curr_yr.i_class_id
> ,curr_yr.i_category_id
> ,curr_yr.i_manufact_id
> ,prev_yr.sales_cnt AS prev_yr_cnt
> ,curr_yr.sales_cnt AS curr_yr_cnt
> ,curr_yr.sales_cnt-prev_yr.sales_cnt AS sales_cnt_diff
> ,curr_yr.sales_amt-prev_yr.sales_amt AS sales_amt_diff
> FROM all_sales curr_yr, all_sales prev_yr
> WHERE curr_yr.i_brand_id=prev_yr.i_brand_id
> AND curr_yr.i_class_id=prev_yr.i_class_id
> AND curr_yr.i_category_id=prev_yr.i_category_id
> AND curr_yr.i_manufact_id=prev_yr.i_manufact_id
> AND curr_yr.d_year=2002
> AND prev_yr.d_year=2002-1
> AND CAST(curr_yr.sales_cnt AS DECIMAL(17,2))/CAST(prev_yr.sales_cnt AS DECIMAL(17,2))<0.9
> ORDER BY sales_cnt_diff
> limit 100
> {code}
> explain
> {code}
> STAGE DEPENDENCIES:
> Stage-1 is a root stage
> Stage-0 depends on stages: Stage-1
> STAGE PLANS:
> Stage: Stage-1
> Tez
> Edges:
> Map 1 <- Map 6 (BROADCAST_EDGE)
> Map 14 <- Map 16 (BROADCAST_EDGE)
> Map 18 <- Reducer 15 (BROADCAST_EDGE), Union 3 (CONTAINS)
> Map 19 <- Map 23 (BROADCAST_EDGE)
> Map 26 <- Map 28 (BROADCAST_EDGE)
> Map 31 <- Map 33 (BROADCAST_EDGE)
> Map 35 <- Reducer 32 (BROADCAST_EDGE), Union 21 (CONTAINS)
> Map 9 <- Map 11 (BROADCAST_EDGE)
> Reducer 10 <- Map 12 (SIMPLE_EDGE), Map 13 (BROADCAST_EDGE), Map 9 (SIMPLE_EDGE), Union 3 (CONTAINS)
> Reducer 15 <- Map 14 (SIMPLE_EDGE), Map 17 (SIMPLE_EDGE)
> Reducer 2 <- Map 1 (SIMPLE_EDGE), Map 7 (SIMPLE_EDGE), Map 8 (BROADCAST_EDGE), Union 3 (CONTAINS)
> Reducer 20 <- Map 19 (SIMPLE_EDGE), Map 24 (SIMPLE_EDGE), Map 25 (BROADCAST_EDGE), Union 21 (CONTAINS)
> Reducer 22 <- Union 21 (SIMPLE_EDGE)
> Reducer 27 <- Map 26 (SIMPLE_EDGE), Map 29 (SIMPLE_EDGE), Map 30 (BROADCAST_EDGE), Union 21 (CONTAINS)
> Reducer 32 <- Map 31 (SIMPLE_EDGE), Map 34 (SIMPLE_EDGE)
> Reducer 4 <- Reducer 22 (BROADCAST_EDGE), Union 3 (SIMPLE_EDGE)
> Reducer 5 <- Reducer 4 (SIMPLE_EDGE)
> DagName: mmokhtar_20150207174141_8f167b31-c893-4c6e-86d6-855d20744d92:1
> Vertices:
> Map 1
> Map Operator Tree:
> TableScan
> alias: catalog_sales
> filterExpr: (cs_sold_date_sk is not null and cs_item_sk is not null) (type: boolean)
> Statistics: Num rows: 817736652 Data size: 16354733056 Basic stats: COMPLETE Column stats: COMPLETE
> Filter Operator
> predicate: (cs_sold_date_sk is not null and cs_item_sk is not null) (type: boolean)
> Statistics: Num rows: 817736652 Data size: 16348976724 Basic stats: COMPLETE Column stats: COMPLETE
> Select Operator
> expressions: cs_sold_date_sk (type: int), cs_item_sk (type: int), cs_order_number (type: int), cs_quantity (type: int), cs_ext_sales_price (type: float)
> outputColumnNames: _col0, _col1, _col2, _col3, _col4
> Statistics: Num rows: 817736652 Data size: 16348976724 Basic stats: COMPLETE Column stats: COMPLETE
> Map Join Operator
> condition map:
> Inner Join 0 to 1
> keys:
> 0 _col0 (type: int)
> 1 _col0 (type: int)
> outputColumnNames: _col1, _col2, _col3, _col4, _col6
> input vertices:
> 1 Map 6
> Statistics: Num rows: 148779579 Data size: 2380473264 Basic stats: COMPLETE Column stats: COMPLETE
> Reduce Output Operator
> key expressions: _col2 (type: int), _col1 (type: int)
> sort order: ++
> Map-reduce partition columns: _col2 (type: int), _col1 (type: int)
> Statistics: Num rows: 148779579 Data size: 2380473264 Basic stats: COMPLETE Column stats: COMPLETE
> value expressions: _col3 (type: int), _col4 (type: float), _col6 (type: int)
> Execution mode: vectorized
> Map 11
> Map Operator Tree:
> TableScan
> alias: date_dim
> filterExpr: ((d_year = 2002) and d_date_sk is not null) (type: boolean)
> Statistics: Num rows: 45363 Data size: 362905 Basic stats: COMPLETE Column stats: COMPLETE
> Filter Operator
> predicate: ((d_year = 2002) and d_date_sk is not null) (type: boolean)
> Statistics: Num rows: 405 Data size: 3240 Basic stats: COMPLETE Column stats: COMPLETE
> Select Operator
> expressions: d_date_sk (type: int)
> outputColumnNames: _col0
> Statistics: Num rows: 405 Data size: 1620 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: 405 Data size: 1620 Basic stats: COMPLETE Column stats: COMPLETE
> value expressions: 2002 (type: int)
> Execution mode: vectorized
> Map 12
> Map Operator Tree:
> TableScan
> alias: store_returns
> filterExpr: sr_item_sk is not null (type: boolean)
> Statistics: Num rows: 167243952 Data size: 2675903232 Basic stats: COMPLETE Column stats: COMPLETE
> Filter Operator
> predicate: sr_item_sk is not null (type: boolean)
> Statistics: Num rows: 167243952 Data size: 2667828428 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: 167243952 Data size: 2667828428 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: 167243952 Data size: 2667828428 Basic stats: COMPLETE Column stats: COMPLETE
> value expressions: _col2 (type: int), _col3 (type: float)
> Execution mode: vectorized
> Map 13
> Map Operator Tree:
> TableScan
> alias: item
> filterExpr: ((((((i_category = 'Sports') and i_item_sk is not null) and i_brand_id is not null) and i_class_id is not null) and i_category_id is not null) and i_manufact_id is not null) (type: boolean)
> Statistics: Num rows: 118835 Data size: 3089722 Basic stats: COMPLETE Column stats: COMPLETE
> Filter Operator
> predicate: ((((((i_category = 'Sports') and i_item_sk is not null) and i_brand_id is not null) and i_class_id is not null) and i_category_id is not null) and i_manufact_id is not null) (type: boolean)
> Statistics: Num rows: 11836 Data size: 1301772 Basic stats: COMPLETE Column stats: COMPLETE
> Select Operator
> expressions: i_item_sk (type: int), i_brand_id (type: int), i_class_id (type: int), i_category_id (type: int), i_manufact_id (type: int)
> outputColumnNames: _col0, _col1, _col2, _col3, _col5
> Statistics: Num rows: 11836 Data size: 236532 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: 11836 Data size: 236532 Basic stats: COMPLETE Column stats: COMPLETE
> value expressions: _col1 (type: int), _col2 (type: int), _col3 (type: int), _col5 (type: int)
> Execution mode: vectorized
> Map 14
> Map Operator Tree:
> TableScan
> alias: web_sales
> filterExpr: (ws_sold_date_sk is not null and ws_item_sk is not null) (type: boolean)
> Statistics: Num rows: 447759411 Data size: 8955188224 Basic stats: COMPLETE Column stats: COMPLETE
> Filter Operator
> predicate: (ws_sold_date_sk is not null and ws_item_sk is not null) (type: boolean)
> Statistics: Num rows: 447759411 Data size: 8955044072 Basic stats: COMPLETE Column stats: COMPLETE
> Select Operator
> expressions: ws_sold_date_sk (type: int), ws_item_sk (type: int), ws_order_number (type: int), ws_quantity (type: int), ws_ext_sales_price (type: float)
> outputColumnNames: _col0, _col1, _col2, _col3, _col4
> Statistics: Num rows: 447759411 Data size: 8955044072 Basic stats: COMPLETE Column stats: COMPLETE
> Map Join Operator
> condition map:
> Inner Join 0 to 1
> keys:
> 0 _col0 (type: int)
> 1 _col0 (type: int)
> outputColumnNames: _col1, _col2, _col3, _col4, _col6
> input vertices:
> 1 Map 16
> Statistics: Num rows: 81465661 Data size: 1303450576 Basic stats: COMPLETE Column stats: COMPLETE
> Reduce Output Operator
> key expressions: _col2 (type: int), _col1 (type: int)
> sort order: ++
> Map-reduce partition columns: _col2 (type: int), _col1 (type: int)
> Statistics: Num rows: 81465661 Data size: 1303450576 Basic stats: COMPLETE Column stats: COMPLETE
> value expressions: _col3 (type: int), _col4 (type: float), _col6 (type: int)
> Execution mode: vectorized
> Map 16
> Map Operator Tree:
> TableScan
> alias: date_dim
> filterExpr: ((d_year = 2002) and d_date_sk is not null) (type: boolean)
> Statistics: Num rows: 45363 Data size: 362905 Basic stats: COMPLETE Column stats: COMPLETE
> Filter Operator
> predicate: ((d_year = 2002) and d_date_sk is not null) (type: boolean)
> Statistics: Num rows: 405 Data size: 3240 Basic stats: COMPLETE Column stats: COMPLETE
> Select Operator
> expressions: d_date_sk (type: int)
> outputColumnNames: _col0
> Statistics: Num rows: 405 Data size: 1620 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: 405 Data size: 1620 Basic stats: COMPLETE Column stats: COMPLETE
> value expressions: 2002 (type: int)
> Execution mode: vectorized
> Map 17
> Map Operator Tree:
> TableScan
> alias: web_returns
> filterExpr: wr_item_sk is not null (type: boolean)
> Statistics: Num rows: 50457044 Data size: 807312704 Basic stats: COMPLETE Column stats: COMPLETE
> Filter Operator
> predicate: wr_item_sk is not null (type: boolean)
> Statistics: Num rows: 50457044 Data size: 804725540 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: 50457044 Data size: 804725540 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: 50457044 Data size: 804725540 Basic stats: COMPLETE Column stats: COMPLETE
> value expressions: _col2 (type: int), _col3 (type: float)
> Execution mode: vectorized
> Map 18
> Map Operator Tree:
> TableScan
> alias: item
> filterExpr: ((((((i_category = 'Sports') and i_item_sk is not null) and i_brand_id is not null) and i_class_id is not null) and i_category_id is not null) and i_manufact_id is not null) (type: boolean)
> Filter Operator
> predicate: ((((((i_category = 'Sports') and i_item_sk is not null) and i_brand_id is not null) and i_class_id is not null) and i_category_id is not null) and i_manufact_id is not null) (type: boolean)
> Select Operator
> expressions: i_item_sk (type: int), i_brand_id (type: int), i_class_id (type: int), i_category_id (type: int), i_manufact_id (type: int)
> outputColumnNames: _col0, _col1, _col2, _col3, _col5
> Map Join Operator
> condition map:
> Inner Join 0 to 1
> keys:
> 0 _col1 (type: int)
> 1 _col0 (type: int)
> outputColumnNames: _col3, _col4, _col6, _col9, _col10, _col12, _col13, _col14, _col16
> input vertices:
> 0 Reducer 15
> Select Operator
> expressions: _col6 (type: int), _col12 (type: int), _col13 (type: int), _col14 (type: int), _col16 (type: int), (_col3 - COALESCE(_col9,0)) (type: int), (UDFToDouble(_col4) - COALESCE(_col10,0.0)) (type: double)
> outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6
> Group By Operator
> aggregations: sum(_col5), sum(_col6)
> keys: _col0 (type: int), _col1 (type: int), _col2 (type: int), _col3 (type: int), _col4 (type: int)
> mode: hash
> outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6
> Reduce Output Operator
> key expressions: _col0 (type: int), _col1 (type: int), _col2 (type: int), _col3 (type: int), _col4 (type: int)
> sort order: +++++
> Map-reduce partition columns: _col0 (type: int), _col1 (type: int), _col2 (type: int), _col3 (type: int), _col4 (type: int)
> value expressions: _col5 (type: bigint), _col6 (type: double)
> Execution mode: vectorized
> Map 19
> Map Operator Tree:
> TableScan
> alias: catalog_sales
> filterExpr: (cs_sold_date_sk is not null and cs_item_sk is not null) (type: boolean)
> Statistics: Num rows: 817736652 Data size: 16354733056 Basic stats: COMPLETE Column stats: COMPLETE
> Filter Operator
> predicate: (cs_sold_date_sk is not null and cs_item_sk is not null) (type: boolean)
> Statistics: Num rows: 817736652 Data size: 16348976724 Basic stats: COMPLETE Column stats: COMPLETE
> Select Operator
> expressions: cs_sold_date_sk (type: int), cs_item_sk (type: int), cs_order_number (type: int), cs_quantity (type: int), cs_ext_sales_price (type: float)
> outputColumnNames: _col0, _col1, _col2, _col3, _col4
> Statistics: Num rows: 817736652 Data size: 16348976724 Basic stats: COMPLETE Column stats: COMPLETE
> Map Join Operator
> condition map:
> Inner Join 0 to 1
> keys:
> 0 _col0 (type: int)
> 1 _col0 (type: int)
> outputColumnNames: _col1, _col2, _col3, _col4, _col6
> input vertices:
> 1 Map 23
> Statistics: Num rows: 148779579 Data size: 2380473264 Basic stats: COMPLETE Column stats: COMPLETE
> Reduce Output Operator
> key expressions: _col2 (type: int), _col1 (type: int)
> sort order: ++
> Map-reduce partition columns: _col2 (type: int), _col1 (type: int)
> Statistics: Num rows: 148779579 Data size: 2380473264 Basic stats: COMPLETE Column stats: COMPLETE
> value expressions: _col3 (type: int), _col4 (type: float), _col6 (type: int)
> Execution mode: vectorized
> Map 23
> Map Operator Tree:
> TableScan
> alias: date_dim
> filterExpr: ((d_year = 2001) and d_date_sk is not null) (type: boolean)
> Statistics: Num rows: 45363 Data size: 362905 Basic stats: COMPLETE Column stats: COMPLETE
> Filter Operator
> predicate: ((d_year = 2001) and d_date_sk is not null) (type: boolean)
> Statistics: Num rows: 405 Data size: 3240 Basic stats: COMPLETE Column stats: COMPLETE
> Select Operator
> expressions: d_date_sk (type: int)
> outputColumnNames: _col0
> Statistics: Num rows: 405 Data size: 1620 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: 405 Data size: 1620 Basic stats: COMPLETE Column stats: COMPLETE
> value expressions: 2001 (type: int)
> Execution mode: vectorized
> Map 24
> Map Operator Tree:
> TableScan
> alias: catalog_returns
> filterExpr: cr_item_sk is not null (type: boolean)
> Statistics: Num rows: 108409176 Data size: 1734546816 Basic stats: COMPLETE Column stats: COMPLETE
> Filter Operator
> predicate: cr_item_sk is not null (type: boolean)
> Statistics: Num rows: 108409176 Data size: 1729935996 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: 108409176 Data size: 1729935996 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: 108409176 Data size: 1729935996 Basic stats: COMPLETE Column stats: COMPLETE
> value expressions: _col2 (type: int), _col3 (type: float)
> Execution mode: vectorized
> Map 25
> Map Operator Tree:
> TableScan
> alias: item
> filterExpr: ((((((i_category = 'Sports') and i_item_sk is not null) and i_brand_id is not null) and i_class_id is not null) and i_category_id is not null) and i_manufact_id is not null) (type: boolean)
> Statistics: Num rows: 118835 Data size: 3089722 Basic stats: COMPLETE Column stats: COMPLETE
> Filter Operator
> predicate: ((((((i_category = 'Sports') and i_item_sk is not null) and i_brand_id is not null) and i_class_id is not null) and i_category_id is not null) and i_manufact_id is not null) (type: boolean)
> Statistics: Num rows: 11836 Data size: 1301772 Basic stats: COMPLETE Column stats: COMPLETE
> Select Operator
> expressions: i_item_sk (type: int), i_brand_id (type: int), i_class_id (type: int), i_category_id (type: int), i_manufact_id (type: int)
> outputColumnNames: _col0, _col1, _col2, _col3, _col5
> Statistics: Num rows: 11836 Data size: 236532 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: 11836 Data size: 236532 Basic stats: COMPLETE Column stats: COMPLETE
> value expressions: _col1 (type: int), _col2 (type: int), _col3 (type: int), _col5 (type: int)
> Execution mode: vectorized
> Map 26
> Map Operator Tree:
> TableScan
> alias: store_sales
> filterExpr: (ss_sold_date_sk is not null and ss_item_sk is not null) (type: boolean)
> Statistics: Num rows: 1174353612 Data size: 23487072256 Basic stats: COMPLETE Column stats: COMPLETE
> Filter Operator
> predicate: (ss_sold_date_sk is not null and ss_item_sk is not null) (type: boolean)
> Statistics: Num rows: 1174353612 Data size: 23383406888 Basic stats: COMPLETE Column stats: COMPLETE
> Select Operator
> expressions: ss_sold_date_sk (type: int), ss_item_sk (type: int), ss_ticket_number (type: int), ss_quantity (type: int), ss_ext_sales_price (type: float)
> outputColumnNames: _col0, _col1, _col2, _col3, _col4
> Statistics: Num rows: 1174353612 Data size: 23383406888 Basic stats: COMPLETE Column stats: COMPLETE
> Map Join Operator
> condition map:
> Inner Join 0 to 1
> keys:
> 0 _col0 (type: int)
> 1 _col0 (type: int)
> outputColumnNames: _col1, _col2, _col3, _col4, _col6
> input vertices:
> 1 Map 28
> Statistics: Num rows: 213662719 Data size: 3418603504 Basic stats: COMPLETE Column stats: COMPLETE
> Reduce Output Operator
> key expressions: _col2 (type: int), _col1 (type: int)
> sort order: ++
> Map-reduce partition columns: _col2 (type: int), _col1 (type: int)
> Statistics: Num rows: 213662719 Data size: 3418603504 Basic stats: COMPLETE Column stats: COMPLETE
> value expressions: _col3 (type: int), _col4 (type: float), _col6 (type: int)
> Execution mode: vectorized
> Map 28
> Map Operator Tree:
> TableScan
> alias: date_dim
> filterExpr: ((d_year = 2001) and d_date_sk is not null) (type: boolean)
> Statistics: Num rows: 45363 Data size: 362905 Basic stats: COMPLETE Column stats: COMPLETE
> Filter Operator
> predicate: ((d_year = 2001) and d_date_sk is not null) (type: boolean)
> Statistics: Num rows: 405 Data size: 3240 Basic stats: COMPLETE Column stats: COMPLETE
> Select Operator
> expressions: d_date_sk (type: int)
> outputColumnNames: _col0
> Statistics: Num rows: 405 Data size: 1620 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: 405 Data size: 1620 Basic stats: COMPLETE Column stats: COMPLETE
> value expressions: 2001 (type: int)
> Execution mode: vectorized
> Map 29
> Map Operator Tree:
> TableScan
> alias: store_returns
> filterExpr: sr_item_sk is not null (type: boolean)
> Statistics: Num rows: 167243952 Data size: 2675903232 Basic stats: COMPLETE Column stats: COMPLETE
> Filter Operator
> predicate: sr_item_sk is not null (type: boolean)
> Statistics: Num rows: 167243952 Data size: 2667828428 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: 167243952 Data size: 2667828428 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: 167243952 Data size: 2667828428 Basic stats: COMPLETE Column stats: COMPLETE
> value expressions: _col2 (type: int), _col3 (type: float)
> Execution mode: vectorized
> Map 30
> Map Operator Tree:
> TableScan
> alias: item
> filterExpr: ((((((i_category = 'Sports') and i_item_sk is not null) and i_brand_id is not null) and i_class_id is not null) and i_category_id is not null) and i_manufact_id is not null) (type: boolean)
> Statistics: Num rows: 118835 Data size: 3089722 Basic stats: COMPLETE Column stats: COMPLETE
> Filter Operator
> predicate: ((((((i_category = 'Sports') and i_item_sk is not null) and i_brand_id is not null) and i_class_id is not null) and i_category_id is not null) and i_manufact_id is not null) (type: boolean)
> Statistics: Num rows: 11836 Data size: 1301772 Basic stats: COMPLETE Column stats: COMPLETE
> Select Operator
> expressions: i_item_sk (type: int), i_brand_id (type: int), i_class_id (type: int), i_category_id (type: int), i_manufact_id (type: int)
> outputColumnNames: _col0, _col1, _col2, _col3, _col5
> Statistics: Num rows: 11836 Data size: 236532 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: 11836 Data size: 236532 Basic stats: COMPLETE Column stats: COMPLETE
> value expressions: _col1 (type: int), _col2 (type: int), _col3 (type: int), _col5 (type: int)
> Execution mode: vectorized
> Map 31
> Map Operator Tree:
> TableScan
> alias: web_sales
> filterExpr: (ws_sold_date_sk is not null and ws_item_sk is not null) (type: boolean)
> Statistics: Num rows: 447759411 Data size: 8955188224 Basic stats: COMPLETE Column stats: COMPLETE
> Filter Operator
> predicate: (ws_sold_date_sk is not null and ws_item_sk is not null) (type: boolean)
> Statistics: Num rows: 447759411 Data size: 8955044072 Basic stats: COMPLETE Column stats: COMPLETE
> Select Operator
> expressions: ws_sold_date_sk (type: int), ws_item_sk (type: int), ws_order_number (type: int), ws_quantity (type: int), ws_ext_sales_price (type: float)
> outputColumnNames: _col0, _col1, _col2, _col3, _col4
> Statistics: Num rows: 447759411 Data size: 8955044072 Basic stats: COMPLETE Column stats: COMPLETE
> Map Join Operator
> condition map:
> Inner Join 0 to 1
> keys:
> 0 _col0 (type: int)
> 1 _col0 (type: int)
> outputColumnNames: _col1, _col2, _col3, _col4, _col6
> input vertices:
> 1 Map 33
> Statistics: Num rows: 81465661 Data size: 1303450576 Basic stats: COMPLETE Column stats: COMPLETE
> Reduce Output Operator
> key expressions: _col2 (type: int), _col1 (type: int)
> sort order: ++
> Map-reduce partition columns: _col2 (type: int), _col1 (type: int)
> Statistics: Num rows: 81465661 Data size: 1303450576 Basic stats: COMPLETE Column stats: COMPLETE
> value expressions: _col3 (type: int), _col4 (type: float), _col6 (type: int)
> Execution mode: vectorized
> Map 33
> Map Operator Tree:
> TableScan
> alias: date_dim
> filterExpr: ((d_year = 2001) and d_date_sk is not null) (type: boolean)
> Statistics: Num rows: 45363 Data size: 362905 Basic stats: COMPLETE Column stats: COMPLETE
> Filter Operator
> predicate: ((d_year = 2001) and d_date_sk is not null) (type: boolean)
> Statistics: Num rows: 405 Data size: 3240 Basic stats: COMPLETE Column stats: COMPLETE
> Select Operator
> expressions: d_date_sk (type: int)
> outputColumnNames: _col0
> Statistics: Num rows: 405 Data size: 1620 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: 405 Data size: 1620 Basic stats: COMPLETE Column stats: COMPLETE
> value expressions: 2001 (type: int)
> Execution mode: vectorized
> Map 34
> Map Operator Tree:
> TableScan
> alias: web_returns
> filterExpr: wr_item_sk is not null (type: boolean)
> Statistics: Num rows: 50457044 Data size: 807312704 Basic stats: COMPLETE Column stats: COMPLETE
> Filter Operator
> predicate: wr_item_sk is not null (type: boolean)
> Statistics: Num rows: 50457044 Data size: 804725540 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: 50457044 Data size: 804725540 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: 50457044 Data size: 804725540 Basic stats: COMPLETE Column stats: COMPLETE
> value expressions: _col2 (type: int), _col3 (type: float)
> Execution mode: vectorized
> Map 35
> Map Operator Tree:
> TableScan
> alias: item
> filterExpr: ((((((i_category = 'Sports') and i_item_sk is not null) and i_brand_id is not null) and i_class_id is not null) and i_category_id is not null) and i_manufact_id is not null) (type: boolean)
> Filter Operator
> predicate: ((((((i_category = 'Sports') and i_item_sk is not null) and i_brand_id is not null) and i_class_id is not null) and i_category_id is not null) and i_manufact_id is not null) (type: boolean)
> Select Operator
> expressions: i_item_sk (type: int), i_brand_id (type: int), i_class_id (type: int), i_category_id (type: int), i_manufact_id (type: int)
> outputColumnNames: _col0, _col1, _col2, _col3, _col5
> Map Join Operator
> condition map:
> Inner Join 0 to 1
> keys:
> 0 _col1 (type: int)
> 1 _col0 (type: int)
> outputColumnNames: _col3, _col4, _col6, _col9, _col10, _col12, _col13, _col14, _col16
> input vertices:
> 0 Reducer 32
> Select Operator
> expressions: _col6 (type: int), _col12 (type: int), _col13 (type: int), _col14 (type: int), _col16 (type: int), (_col3 - COALESCE(_col9,0)) (type: int), (UDFToDouble(_col4) - COALESCE(_col10,0.0)) (type: double)
> outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6
> Group By Operator
> aggregations: sum(_col5), sum(_col6)
> keys: _col0 (type: int), _col1 (type: int), _col2 (type: int), _col3 (type: int), _col4 (type: int)
> mode: hash
> outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6
> Reduce Output Operator
> key expressions: _col0 (type: int), _col1 (type: int), _col2 (type: int), _col3 (type: int), _col4 (type: int)
> sort order: +++++
> Map-reduce partition columns: _col0 (type: int), _col1 (type: int), _col2 (type: int), _col3 (type: int), _col4 (type: int)
> value expressions: _col5 (type: bigint), _col6 (type: double)
> Execution mode: vectorized
> Map 6
> Map Operator Tree:
> TableScan
> alias: date_dim
> filterExpr: ((d_year = 2002) and d_date_sk is not null) (type: boolean)
> Statistics: Num rows: 45363 Data size: 362905 Basic stats: COMPLETE Column stats: COMPLETE
> Filter Operator
> predicate: ((d_year = 2002) and d_date_sk is not null) (type: boolean)
> Statistics: Num rows: 405 Data size: 3240 Basic stats: COMPLETE Column stats: COMPLETE
> Select Operator
> expressions: d_date_sk (type: int)
> outputColumnNames: _col0
> Statistics: Num rows: 405 Data size: 1620 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: 405 Data size: 1620 Basic stats: COMPLETE Column stats: COMPLETE
> value expressions: 2002 (type: int)
> Execution mode: vectorized
> Map 7
> Map Operator Tree:
> TableScan
> alias: catalog_returns
> filterExpr: cr_item_sk is not null (type: boolean)
> Statistics: Num rows: 108409176 Data size: 1734546816 Basic stats: COMPLETE Column stats: COMPLETE
> Filter Operator
> predicate: cr_item_sk is not null (type: boolean)
> Statistics: Num rows: 108409176 Data size: 1729935996 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: 108409176 Data size: 1729935996 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: 108409176 Data size: 1729935996 Basic stats: COMPLETE Column stats: COMPLETE
> value expressions: _col2 (type: int), _col3 (type: float)
> Execution mode: vectorized
> Map 8
> Map Operator Tree:
> TableScan
> alias: item
> filterExpr: ((((((i_category = 'Sports') and i_item_sk is not null) and i_brand_id is not null) and i_class_id is not null) and i_category_id is not null) and i_manufact_id is not null) (type: boolean)
> Statistics: Num rows: 118835 Data size: 3089722 Basic stats: COMPLETE Column stats: COMPLETE
> Filter Operator
> predicate: ((((((i_category = 'Sports') and i_item_sk is not null) and i_brand_id is not null) and i_class_id is not null) and i_category_id is not null) and i_manufact_id is not null) (type: boolean)
> Statistics: Num rows: 11836 Data size: 1301772 Basic stats: COMPLETE Column stats: COMPLETE
> Select Operator
> expressions: i_item_sk (type: int), i_brand_id (type: int), i_class_id (type: int), i_category_id (type: int), i_manufact_id (type: int)
> outputColumnNames: _col0, _col1, _col2, _col3, _col5
> Statistics: Num rows: 11836 Data size: 236532 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: 11836 Data size: 236532 Basic stats: COMPLETE Column stats: COMPLETE
> value expressions: _col1 (type: int), _col2 (type: int), _col3 (type: int), _col5 (type: int)
> Execution mode: vectorized
> Map 9
> Map Operator Tree:
> TableScan
> alias: store_sales
> filterExpr: (ss_sold_date_sk is not null and ss_item_sk is not null) (type: boolean)
> Statistics: Num rows: 1174353612 Data size: 23487072256 Basic stats: COMPLETE Column stats: COMPLETE
> Filter Operator
> predicate: (ss_sold_date_sk is not null and ss_item_sk is not null) (type: boolean)
> Statistics: Num rows: 1174353612 Data size: 23383406888 Basic stats: COMPLETE Column stats: COMPLETE
> Select Operator
> expressions: ss_sold_date_sk (type: int), ss_item_sk (type: int), ss_ticket_number (type: int), ss_quantity (type: int), ss_ext_sales_price (type: float)
> outputColumnNames: _col0, _col1, _col2, _col3, _col4
> Statistics: Num rows: 1174353612 Data size: 23383406888 Basic stats: COMPLETE Column stats: COMPLETE
> Map Join Operator
> condition map:
> Inner Join 0 to 1
> keys:
> 0 _col0 (type: int)
> 1 _col0 (type: int)
> outputColumnNames: _col1, _col2, _col3, _col4, _col6
> input vertices:
> 1 Map 11
> Statistics: Num rows: 213662719 Data size: 3418603504 Basic stats: COMPLETE Column stats: COMPLETE
> Reduce Output Operator
> key expressions: _col2 (type: int), _col1 (type: int)
> sort order: ++
> Map-reduce partition columns: _col2 (type: int), _col1 (type: int)
> Statistics: Num rows: 213662719 Data size: 3418603504 Basic stats: COMPLETE Column stats: COMPLETE
> value expressions: _col3 (type: int), _col4 (type: float), _col6 (type: int)
> Execution mode: vectorized
> Reducer 10
> Reduce Operator Tree:
> Merge Join Operator
> condition map:
> Left Outer Join0 to 1
> keys:
> 0 _col2 (type: int), _col1 (type: int)
> 1 _col1 (type: int), _col0 (type: int)
> outputColumnNames: _col1, _col3, _col4, _col6, _col9, _col10
> Map Join Operator
> condition map:
> Inner Join 0 to 1
> keys:
> 0 _col1 (type: int)
> 1 _col0 (type: int)
> outputColumnNames: _col3, _col4, _col6, _col9, _col10, _col12, _col13, _col14, _col16
> input vertices:
> 1 Map 13
> Select Operator
> expressions: _col6 (type: int), _col12 (type: int), _col13 (type: int), _col14 (type: int), _col16 (type: int), (_col3 - COALESCE(_col9,0)) (type: int), (UDFToDouble(_col4) - COALESCE(_col10,0.0)) (type: double)
> outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6
> Group By Operator
> aggregations: sum(_col5), sum(_col6)
> keys: _col0 (type: int), _col1 (type: int), _col2 (type: int), _col3 (type: int), _col4 (type: int)
> mode: hash
> outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6
> Reduce Output Operator
> key expressions: _col0 (type: int), _col1 (type: int), _col2 (type: int), _col3 (type: int), _col4 (type: int)
> sort order: +++++
> Map-reduce partition columns: _col0 (type: int), _col1 (type: int), _col2 (type: int), _col3 (type: int), _col4 (type: int)
> value expressions: _col5 (type: bigint), _col6 (type: double)
> Reducer 15
> Reduce Operator Tree:
> Merge Join Operator
> condition map:
> Left Outer Join0 to 1
> keys:
> 0 _col2 (type: int), _col1 (type: int)
> 1 _col1 (type: int), _col0 (type: int)
> outputColumnNames: _col1, _col3, _col4, _col6, _col9, _col10
> Statistics: Num rows: 8204 Data size: 164080 Basic stats: COMPLETE Column stats: COMPLETE
> Reduce Output Operator
> key expressions: _col1 (type: int)
> sort order: +
> Map-reduce partition columns: _col1 (type: int)
> Statistics: Num rows: 8204 Data size: 164080 Basic stats: COMPLETE Column stats: COMPLETE
> value expressions: _col3 (type: int), _col4 (type: float), _col6 (type: int), _col9 (type: int), _col10 (type: float)
> Reducer 2
> Reduce Operator Tree:
> Merge Join Operator
> condition map:
> Left Outer Join0 to 1
> keys:
> 0 _col2 (type: int), _col1 (type: int)
> 1 _col1 (type: int), _col0 (type: int)
> outputColumnNames: _col1, _col3, _col4, _col6, _col9, _col10
> Map Join Operator
> condition map:
> Inner Join 0 to 1
> keys:
> 0 _col1 (type: int)
> 1 _col0 (type: int)
> outputColumnNames: _col3, _col4, _col6, _col9, _col10, _col12, _col13, _col14, _col16
> input vertices:
> 1 Map 8
> Select Operator
> expressions: _col6 (type: int), _col12 (type: int), _col13 (type: int), _col14 (type: int), _col16 (type: int), (_col3 - COALESCE(_col9,0)) (type: int), (UDFToDouble(_col4) - COALESCE(_col10,0.0)) (type: double)
> outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6
> Group By Operator
> aggregations: sum(_col5), sum(_col6)
> keys: _col0 (type: int), _col1 (type: int), _col2 (type: int), _col3 (type: int), _col4 (type: int)
> mode: hash
> outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6
> Reduce Output Operator
> key expressions: _col0 (type: int), _col1 (type: int), _col2 (type: int), _col3 (type: int), _col4 (type: int)
> sort order: +++++
> Map-reduce partition columns: _col0 (type: int), _col1 (type: int), _col2 (type: int), _col3 (type: int), _col4 (type: int)
> value expressions: _col5 (type: bigint), _col6 (type: double)
> Reducer 20
> Reduce Operator Tree:
> Merge Join Operator
> condition map:
> Left Outer Join0 to 1
> keys:
> 0 _col2 (type: int), _col1 (type: int)
> 1 _col1 (type: int), _col0 (type: int)
> outputColumnNames: _col1, _col3, _col4, _col6, _col9, _col10
> Map Join Operator
> condition map:
> Inner Join 0 to 1
> keys:
> 0 _col1 (type: int)
> 1 _col0 (type: int)
> outputColumnNames: _col3, _col4, _col6, _col9, _col10, _col12, _col13, _col14, _col16
> input vertices:
> 1 Map 25
> Select Operator
> expressions: _col6 (type: int), _col12 (type: int), _col13 (type: int), _col14 (type: int), _col16 (type: int), (_col3 - COALESCE(_col9,0)) (type: int), (UDFToDouble(_col4) - COALESCE(_col10,0.0)) (type: double)
> outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6
> Group By Operator
> aggregations: sum(_col5), sum(_col6)
> keys: _col0 (type: int), _col1 (type: int), _col2 (type: int), _col3 (type: int), _col4 (type: int)
> mode: hash
> outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6
> Reduce Output Operator
> key expressions: _col0 (type: int), _col1 (type: int), _col2 (type: int), _col3 (type: int), _col4 (type: int)
> sort order: +++++
> Map-reduce partition columns: _col0 (type: int), _col1 (type: int), _col2 (type: int), _col3 (type: int), _col4 (type: int)
> value expressions: _col5 (type: bigint), _col6 (type: double)
> Reducer 22
> Reduce Operator Tree:
> Group By Operator
> aggregations: sum(VALUE._col0), sum(VALUE._col1)
> keys: KEY._col0 (type: int), KEY._col1 (type: int), KEY._col2 (type: int), KEY._col3 (type: int), KEY._col4 (type: int)
> mode: mergepartial
> outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6
> Statistics: Num rows: 1 Data size: 16 Basic stats: COMPLETE Column stats: COMPLETE
> Reduce Output Operator
> key expressions: _col1 (type: int), _col2 (type: int), _col3 (type: int), _col4 (type: int)
> sort order: ++++
> Map-reduce partition columns: _col1 (type: int), _col2 (type: int), _col3 (type: int), _col4 (type: int)
> Statistics: Num rows: 1 Data size: 16 Basic stats: COMPLETE Column stats: COMPLETE
> value expressions: _col0 (type: int), _col5 (type: bigint), _col6 (type: double)
> Reducer 27
> Reduce Operator Tree:
> Merge Join Operator
> condition map:
> Left Outer Join0 to 1
> keys:
> 0 _col2 (type: int), _col1 (type: int)
> 1 _col1 (type: int), _col0 (type: int)
> outputColumnNames: _col1, _col3, _col4, _col6, _col9, _col10
> Map Join Operator
> condition map:
> Inner Join 0 to 1
> keys:
> 0 _col1 (type: int)
> 1 _col0 (type: int)
> outputColumnNames: _col3, _col4, _col6, _col9, _col10, _col12, _col13, _col14, _col16
> input vertices:
> 1 Map 30
> Select Operator
> expressions: _col6 (type: int), _col12 (type: int), _col13 (type: int), _col14 (type: int), _col16 (type: int), (_col3 - COALESCE(_col9,0)) (type: int), (UDFToDouble(_col4) - COALESCE(_col10,0.0)) (type: double)
> outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6
> Group By Operator
> aggregations: sum(_col5), sum(_col6)
> keys: _col0 (type: int), _col1 (type: int), _col2 (type: int), _col3 (type: int), _col4 (type: int)
> mode: hash
> outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6
> Reduce Output Operator
> key expressions: _col0 (type: int), _col1 (type: int), _col2 (type: int), _col3 (type: int), _col4 (type: int)
> sort order: +++++
> Map-reduce partition columns: _col0 (type: int), _col1 (type: int), _col2 (type: int), _col3 (type: int), _col4 (type: int)
> value expressions: _col5 (type: bigint), _col6 (type: double)
> Reducer 32
> Reduce Operator Tree:
> Merge Join Operator
> condition map:
> Left Outer Join0 to 1
> keys:
> 0 _col2 (type: int), _col1 (type: int)
> 1 _col1 (type: int), _col0 (type: int)
> outputColumnNames: _col1, _col3, _col4, _col6, _col9, _col10
> Statistics: Num rows: 8204 Data size: 164080 Basic stats: COMPLETE Column stats: COMPLETE
> Reduce Output Operator
> key expressions: _col1 (type: int)
> sort order: +
> Map-reduce partition columns: _col1 (type: int)
> Statistics: Num rows: 8204 Data size: 164080 Basic stats: COMPLETE Column stats: COMPLETE
> value expressions: _col3 (type: int), _col4 (type: float), _col6 (type: int), _col9 (type: int), _col10 (type: float)
> Reducer 4
> Reduce Operator Tree:
> Group By Operator
> aggregations: sum(VALUE._col0), sum(VALUE._col1)
> keys: KEY._col0 (type: int), KEY._col1 (type: int), KEY._col2 (type: int), KEY._col3 (type: int), KEY._col4 (type: int)
> mode: mergepartial
> outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6
> Statistics: Num rows: 1 Data size: 16 Basic stats: COMPLETE Column stats: COMPLETE
> Map Join Operator
> condition map:
> Inner Join 0 to 1
> keys:
> 0 _col1 (type: int), _col2 (type: int), _col3 (type: int), _col4 (type: int)
> 1 _col1 (type: int), _col2 (type: int), _col3 (type: int), _col4 (type: int)
> outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col12, _col13
> input vertices:
> 1 Reducer 22
> Statistics: Num rows: 0 Data size: 0 Basic stats: NONE Column stats: COMPLETE
> Filter Operator
> predicate: ((CAST( _col5 AS decimal(17,2)) / CAST( _col12 AS decimal(17,2))) < CAST( 0.9 AS decimal(37,20))) (type: boolean)
> Statistics: Num rows: 0 Data size: 0 Basic stats: NONE Column stats: COMPLETE
> Select Operator
> expressions: _col7 (type: int), _col0 (type: int), _col1 (type: int), _col2 (type: int), _col3 (type: int), _col4 (type: int), _col12 (type: bigint), _col5 (type: bigint), (_col5 - _col12) (type: bigint), (_col6 - _col13) (type: double)
> outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9
> Statistics: Num rows: 0 Data size: 0 Basic stats: NONE Column stats: COMPLETE
> Reduce Output Operator
> key expressions: _col8 (type: bigint)
> sort order: +
> Statistics: Num rows: 0 Data size: 0 Basic stats: NONE Column stats: COMPLETE
> TopN Hash Memory Usage: 0.04
> value expressions: _col0 (type: int), _col1 (type: int), _col2 (type: int), _col3 (type: int), _col4 (type: int), _col5 (type: int), _col6 (type: bigint), _col7 (type: bigint), _col9 (type: double)
> Reducer 5
> Reduce Operator Tree:
> Select Operator
> expressions: VALUE._col0 (type: int), VALUE._col1 (type: int), VALUE._col2 (type: int), VALUE._col3 (type: int), VALUE._col4 (type: int), VALUE._col5 (type: int), VALUE._col6 (type: bigint), VALUE._col7 (type: bigint), KEY.reducesinkkey0 (type: bigint), VALUE._col8 (type: double)
> outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9
> Statistics: Num rows: 0 Data size: 0 Basic stats: NONE Column stats: COMPLETE
> Limit
> Number of rows: 100
> Statistics: Num rows: 0 Data size: 0 Basic stats: NONE Column stats: COMPLETE
> File Output Operator
> compressed: false
> Statistics: Num rows: 0 Data size: 0 Basic stats: NONE Column stats: COMPLETE
> 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 21
> Vertex: Union 21
> Union 3
> Vertex: Union 3
> Stage: Stage-0
> Fetch Operator
> limit: 100
> Processor Tree:
> ListSink
> Time taken: 12.351 seconds, Fetched: 821 row(s)
> {code}
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