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https://issues.apache.org/jira/browse/HIVE-17178?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16362509#comment-16362509
]
Hive QA commented on HIVE-17178:
--------------------------------
Here are the results of testing the latest attachment:
https://issues.apache.org/jira/secure/attachment/12910336/HIVE-17178.3.patch
{color:green}SUCCESS:{color} +1 due to 1 test(s) being added or modified.
{color:red}ERROR:{color} -1 due to 28 failed/errored test(s), 13174 tests
executed
*Failed tests:*
{noformat}
org.apache.hadoop.hive.cli.TestAccumuloCliDriver.testCliDriver[accumulo_queries]
(batchId=241)
org.apache.hadoop.hive.cli.TestCliDriver.testCliDriver[mapjoin_hook]
(batchId=13)
org.apache.hadoop.hive.cli.TestCliDriver.testCliDriver[ppd_join5] (batchId=36)
org.apache.hadoop.hive.cli.TestCliDriver.testCliDriver[row__id] (batchId=79)
org.apache.hadoop.hive.cli.TestEncryptedHDFSCliDriver.testCliDriver[encryption_move_tbl]
(batchId=175)
org.apache.hadoop.hive.cli.TestMiniLlapCliDriver.testCliDriver[llap_smb]
(batchId=152)
org.apache.hadoop.hive.cli.TestMiniLlapLocalCliDriver.testCliDriver[bucket_map_join_tez1]
(batchId=172)
org.apache.hadoop.hive.cli.TestMiniLlapLocalCliDriver.testCliDriver[insert_values_orig_table_use_metadata]
(batchId=167)
org.apache.hadoop.hive.cli.TestMiniLlapLocalCliDriver.testCliDriver[llap_acid]
(batchId=171)
org.apache.hadoop.hive.cli.TestMiniLlapLocalCliDriver.testCliDriver[llap_acid_fast]
(batchId=162)
org.apache.hadoop.hive.cli.TestMiniLlapLocalCliDriver.testCliDriver[resourceplan]
(batchId=164)
org.apache.hadoop.hive.cli.TestMiniLlapLocalCliDriver.testCliDriver[results_cache_1]
(batchId=168)
org.apache.hadoop.hive.cli.TestMiniLlapLocalCliDriver.testCliDriver[sysdb]
(batchId=161)
org.apache.hadoop.hive.cli.TestMiniSparkOnYarnCliDriver.testCliDriver[bucketizedhiveinputformat]
(batchId=180)
org.apache.hadoop.hive.cli.TestMiniSparkOnYarnCliDriver.testCliDriver[bucketmapjoin6]
(batchId=180)
org.apache.hadoop.hive.cli.TestMiniSparkOnYarnCliDriver.testCliDriver[dynamic_rdd_cache]
(batchId=180)
org.apache.hadoop.hive.cli.TestMiniSparkOnYarnCliDriver.testCliDriver[spark_dynamic_partition_pruning_6]
(batchId=180)
org.apache.hadoop.hive.cli.TestMiniSparkOnYarnCliDriver.testCliDriver[spark_opt_shuffle_serde]
(batchId=180)
org.apache.hadoop.hive.cli.TestSparkCliDriver.testCliDriver[ppd_join5]
(batchId=122)
org.apache.hadoop.hive.cli.TestSparkPerfCliDriver.testCliDriver[query1]
(batchId=251)
org.apache.hadoop.hive.cli.control.TestDanglingQOuts.checkDanglingQOut
(batchId=222)
org.apache.hadoop.hive.metastore.client.TestTablesGetExists.testGetAllTablesCaseInsensitive[Embedded]
(batchId=206)
org.apache.hadoop.hive.metastore.client.TestTablesList.testListTableNamesByFilterNullDatabase[Embedded]
(batchId=206)
org.apache.hadoop.hive.ql.exec.tez.TestTezTask.testEmptyWork (batchId=287)
org.apache.hive.beeline.cli.TestHiveCli.testNoErrorDB (batchId=188)
org.apache.hive.jdbc.TestSSL.testConnectionMismatch (batchId=235)
org.apache.hive.jdbc.TestSSL.testConnectionWrongCertCN (batchId=235)
org.apache.hive.jdbc.TestSSL.testMetastoreConnectionWrongCertCN (batchId=235)
{noformat}
Test results: https://builds.apache.org/job/PreCommit-HIVE-Build/9191/testReport
Console output: https://builds.apache.org/job/PreCommit-HIVE-Build/9191/console
Test logs: http://104.198.109.242/logs/PreCommit-HIVE-Build-9191/
Messages:
{noformat}
Executing org.apache.hive.ptest.execution.TestCheckPhase
Executing org.apache.hive.ptest.execution.PrepPhase
Executing org.apache.hive.ptest.execution.YetusPhase
Executing org.apache.hive.ptest.execution.ExecutionPhase
Executing org.apache.hive.ptest.execution.ReportingPhase
Tests exited with: TestsFailedException: 28 tests failed
{noformat}
This message is automatically generated.
ATTACHMENT ID: 12910336 - PreCommit-HIVE-Build
> Spark Partition Pruning Sink Operator can't target multiple Works
> -----------------------------------------------------------------
>
> Key: HIVE-17178
> URL: https://issues.apache.org/jira/browse/HIVE-17178
> Project: Hive
> Issue Type: Sub-task
> Components: Spark
> Reporter: Sahil Takiar
> Assignee: Rui Li
> Priority: Major
> Attachments: HIVE-17178.1.patch, HIVE-17178.2.patch,
> HIVE-17178.3.patch
>
>
> A Spark Partition Pruning Sink Operator cannot be used to target multiple Map
> Work objects. The entire DPP subtree (SEL-GBY-SPARKPRUNINGSINK) is duplicated
> if a single table needs to be used to target multiple Map Works.
> The following query shows the issue:
> {code}
> set hive.spark.dynamic.partition.pruning=true;
> set hive.auto.convert.join=true;
> create table part_table_1 (col int) partitioned by (part_col int);
> create table part_table_2 (col int) partitioned by (part_col int);
> create table regular_table (col int);
> insert into table regular_table values (1);
> alter table part_table_1 add partition (part_col=1);
> insert into table part_table_1 partition (part_col=1) values (1), (2), (3),
> (4);
> alter table part_table_1 add partition (part_col=2);
> insert into table part_table_1 partition (part_col=2) values (1), (2), (3),
> (4);
> alter table part_table_2 add partition (part_col=1);
> insert into table part_table_2 partition (part_col=1) values (1), (2), (3),
> (4);
> alter table part_table_2 add partition (part_col=2);
> insert into table part_table_2 partition (part_col=2) values (1), (2), (3),
> (4);
> explain select * from regular_table, part_table_1, part_table_2 where
> regular_table.col = part_table_1.part_col and regular_table.col =
> part_table_2.part_col;
> {code}
> The explain plan is
> {code}
> 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: regular_table
> Statistics: Num rows: 1 Data size: 1 Basic stats: COMPLETE
> Column stats: NONE
> Filter Operator
> predicate: col is not null (type: boolean)
> Statistics: Num rows: 1 Data size: 1 Basic stats:
> COMPLETE Column stats: NONE
> Select Operator
> expressions: col (type: int)
> outputColumnNames: _col0
> Statistics: Num rows: 1 Data size: 1 Basic stats:
> COMPLETE Column stats: NONE
> Spark HashTable Sink Operator
> keys:
> 0 _col0 (type: int)
> 1 _col1 (type: int)
> 2 _col1 (type: int)
> Select Operator
> expressions: _col0 (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
> partition key expr: part_col
> Statistics: Num rows: 1 Data size: 1 Basic stats:
> COMPLETE Column stats: NONE
> target column name: part_col
> target work: Map 2
> Select Operator
> expressions: _col0 (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
> partition key expr: part_col
> Statistics: Num rows: 1 Data size: 1 Basic stats:
> COMPLETE Column stats: NONE
> target column name: part_col
> target work: Map 3
> Local Work:
> Map Reduce Local Work
> Map 3
> Map Operator Tree:
> TableScan
> alias: part_table_2
> Statistics: Num rows: 8 Data size: 8 Basic stats: COMPLETE
> Column stats: NONE
> Select Operator
> expressions: col (type: int), part_col (type: int)
> outputColumnNames: _col0, _col1
> Statistics: Num rows: 8 Data size: 8 Basic stats:
> COMPLETE Column stats: NONE
> Spark HashTable Sink Operator
> keys:
> 0 _col0 (type: int)
> 1 _col1 (type: int)
> 2 _col1 (type: int)
> Select Operator
> expressions: _col1 (type: int)
> outputColumnNames: _col0
> Statistics: Num rows: 8 Data size: 8 Basic stats:
> COMPLETE Column stats: NONE
> Group By Operator
> keys: _col0 (type: int)
> mode: hash
> outputColumnNames: _col0
> Statistics: Num rows: 8 Data size: 8 Basic stats:
> COMPLETE Column stats: NONE
> Spark Partition Pruning Sink Operator
> partition key expr: part_col
> Statistics: Num rows: 8 Data size: 8 Basic stats:
> COMPLETE Column stats: NONE
> target column name: part_col
> target work: Map 2
> Local Work:
> Map Reduce Local Work
> Stage: Stage-1
> Spark
> #### A masked pattern was here ####
> Vertices:
> Map 2
> Map Operator Tree:
> TableScan
> alias: part_table_1
> Statistics: Num rows: 8 Data size: 8 Basic stats: COMPLETE
> Column stats: NONE
> Select Operator
> expressions: col (type: int), part_col (type: int)
> outputColumnNames: _col0, _col1
> Statistics: Num rows: 8 Data size: 8 Basic stats:
> COMPLETE Column stats: NONE
> Map Join Operator
> condition map:
> Inner Join 0 to 1
> Inner Join 0 to 2
> keys:
> 0 _col0 (type: int)
> 1 _col1 (type: int)
> 2 _col1 (type: int)
> outputColumnNames: _col0, _col1, _col2, _col3, _col4
> input vertices:
> 0 Map 1
> 2 Map 3
> Statistics: Num rows: 17 Data size: 17 Basic stats:
> COMPLETE Column stats: NONE
> File Output Operator
> compressed: false
> Statistics: Num rows: 17 Data size: 17 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
> {code}
> The DPP subtrees on Map 1 are exactly the same. We should be able to combine
> them, which avoids doing duplicate work.
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