[
https://issues.apache.org/jira/browse/HIVE-17396?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Janaki Lahorani updated HIVE-17396:
-----------------------------------
Description:
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
> 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
--
This message was sent by Atlassian JIRA
(v6.4.14#64029)
