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https://issues.apache.org/jira/browse/HIVE-17396?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Janaki Lahorani updated HIVE-17396:
-----------------------------------
Status: Patch Available (was: Open)
> Support DPP with map joins where the source and target belong in the same
> stage
> -------------------------------------------------------------------------------
>
> Key: HIVE-17396
> URL: https://issues.apache.org/jira/browse/HIVE-17396
> Project: Hive
> Issue Type: Sub-task
> Components: Spark
> Reporter: Janaki Lahorani
> Assignee: Janaki Lahorani
>
> When the target of a partition pruning sink operator is in not the same as
> the target of hash table sink operator, both source and target gets scheduled
> within the same spark job, and that can result in File Not Found Exception.
> HIVE-17225 has a fix to disable DPP in that scenario. This JIRA is to
> support DPP for such cases.
> Test Case:
> SET hive.spark.dynamic.partition.pruning=true;
> SET hive.auto.convert.join=true;
> SET hive.strict.checks.cartesian.product=false;
> CREATE TABLE part_table1 (col int) PARTITIONED BY (part1_col int);
> CREATE TABLE part_table2 (col int) PARTITIONED BY (part2_col int);
> CREATE TABLE reg_table (col int);
> ALTER TABLE part_table1 ADD PARTITION (part1_col = 1);
> ALTER TABLE part_table2 ADD PARTITION (part2_col = 1);
> ALTER TABLE part_table2 ADD PARTITION (part2_col = 2);
> INSERT INTO TABLE part_table1 PARTITION (part1_col = 1) VALUES (1);
> INSERT INTO TABLE part_table2 PARTITION (part2_col = 1) VALUES (1);
> INSERT INTO TABLE part_table2 PARTITION (part2_col = 2) VALUES (2);
> INSERT INTO table reg_table VALUES (1), (2), (3), (4), (5), (6);
> EXPLAIN SELECT *
> FROM part_table1 pt1,
> part_table2 pt2,
> reg_table rt
> WHERE rt.col = pt1.part1_col
> AND pt2.part2_col = pt1.part1_col;
> Plan:
> STAGE DEPENDENCIES:
> Stage-2 is a root stage
> Stage-1 depends on stages: Stage-2
> Stage-0 depends on stages: Stage-1
> STAGE PLANS:
> Stage: Stage-2
> Spark
> #### A masked pattern was here ####
> Vertices:
> Map 1
> Map Operator Tree:
> TableScan
> alias: pt1
> Statistics: Num rows: 1 Data size: 1 Basic stats: COMPLETE
> Column stats: NONE
> Select Operator
> expressions: col (type: int), part1_col (type: int)
> outputColumnNames: _col0, _col1
> Statistics: Num rows: 1 Data size: 1 Basic stats:
> COMPLETE Column stats: NONE
> Spark HashTable Sink Operator
> keys:
> 0 _col1 (type: int)
> 1 _col1 (type: int)
> 2 _col0 (type: int)
> Select Operator
> expressions: _col1 (type: int)
> outputColumnNames: _col0
> Statistics: Num rows: 1 Data size: 1 Basic stats:
> COMPLETE Column stats: NONE
> Group By Operator
> keys: _col0 (type: int)
> mode: hash
> outputColumnNames: _col0
> Statistics: Num rows: 1 Data size: 1 Basic stats:
> COMPLETE Column stats: NONE
> Spark Partition Pruning Sink Operator
> Target column: part2_col (int)
> partition key expr: part2_col
> Statistics: Num rows: 1 Data size: 1 Basic stats:
> COMPLETE Column stats: NONE
> target work: Map 2
> Local Work:
> Map Reduce Local Work
> Map 2
> Map Operator Tree:
> TableScan
> alias: pt2
> Statistics: Num rows: 2 Data size: 2 Basic stats: COMPLETE
> Column stats: NONE
> Select Operator
> expressions: col (type: int), part2_col (type: int)
> outputColumnNames: _col0, _col1
> Statistics: Num rows: 2 Data size: 2 Basic stats:
> COMPLETE Column stats: NONE
> Spark HashTable Sink Operator
> keys:
> 0 _col1 (type: int)
> 1 _col1 (type: int)
> 2 _col0 (type: int)
> Local Work:
> Map Reduce Local Work
> Stage: Stage-1
> Spark
> #### A masked pattern was here ####
> Vertices:
> Map 3
> Map Operator Tree:
> TableScan
> alias: rt
> Statistics: Num rows: 6 Data size: 6 Basic stats: COMPLETE
> Column stats: NONE
> Filter Operator
> predicate: col is not null (type: boolean)
> Statistics: Num rows: 6 Data size: 6 Basic stats:
> COMPLETE Column stats: NONE
> Select Operator
> expressions: col (type: int)
> outputColumnNames: _col0
> Statistics: Num rows: 6 Data size: 6 Basic stats:
> COMPLETE Column stats: NONE
> Map Join Operator
> condition map:
> Inner Join 0 to 1
> Inner Join 0 to 2
> keys:
> 0 _col1 (type: int)
> 1 _col1 (type: int)
> 2 _col0 (type: int)
> outputColumnNames: _col0, _col1, _col2, _col3, _col4
> input vertices:
> 0 Map 1
> 1 Map 2
> Statistics: Num rows: 13 Data size: 13 Basic stats:
> COMPLETE Column stats: NONE
> File Output Operator
> compressed: false
> Statistics: Num rows: 13 Data size: 13 Basic stats:
> COMPLETE Column stats: NONE
> table:
> input format:
> org.apache.hadoop.mapred.SequenceFileInputFormat
> output format:
> org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat
> serde:
> org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe
> Local Work:
> Map Reduce Local Work
> Stage: Stage-0
> Fetch Operator
> limit: -1
> Processor Tree:
> ListSink
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