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Hive QA commented on HIVE-17178: -------------------------------- | (x) *{color:red}-1 overall{color}* | \\ \\ || Vote || Subsystem || Runtime || Comment || || || || || {color:brown} Prechecks {color} || | {color:blue}0{color} | {color:blue} findbugs {color} | {color:blue} 0m 1s{color} | {color:blue} Findbugs executables are not available. {color} | | {color:green}+1{color} | {color:green} @author {color} | {color:green} 0m 0s{color} | {color:green} The patch does not contain any @author tags. {color} | || || || || {color:brown} master Compile Tests {color} || | {color:blue}0{color} | {color:blue} mvndep {color} | {color:blue} 0m 36s{color} | {color:blue} Maven dependency ordering for branch {color} | | {color:green}+1{color} | {color:green} mvninstall {color} | {color:green} 6m 19s{color} | {color:green} master passed {color} | | {color:green}+1{color} | {color:green} compile {color} | {color:green} 0m 57s{color} | {color:green} master passed {color} | | {color:green}+1{color} | {color:green} checkstyle {color} | {color:green} 0m 37s{color} | {color:green} master passed {color} | | {color:green}+1{color} | {color:green} javadoc {color} | {color:green} 0m 54s{color} | {color:green} master passed {color} | || || || || {color:brown} Patch Compile Tests {color} || | {color:blue}0{color} | {color:blue} mvndep {color} | {color:blue} 0m 8s{color} | {color:blue} Maven dependency ordering for patch {color} | | {color:green}+1{color} | {color:green} mvninstall {color} | {color:green} 1m 14s{color} | {color:green} the patch passed {color} | | {color:green}+1{color} | {color:green} compile {color} | {color:green} 0m 58s{color} | {color:green} the patch passed {color} | | {color:green}+1{color} | {color:green} javac {color} | {color:green} 0m 58s{color} | {color:green} the patch passed {color} | | {color:red}-1{color} | {color:red} checkstyle {color} | {color:red} 0m 38s{color} | {color:red} ql: The patch generated 3 new + 69 unchanged - 3 fixed = 72 total (was 72) {color} | | {color:green}+1{color} | {color:green} whitespace {color} | {color:green} 0m 0s{color} | {color:green} The patch has no whitespace issues. {color} | | {color:green}+1{color} | {color:green} javadoc {color} | {color:green} 0m 55s{color} | {color:green} the patch passed {color} | || || || || {color:brown} Other Tests {color} || | {color:red}-1{color} | {color:red} asflicense {color} | {color:red} 0m 13s{color} | {color:red} The patch generated 49 ASF License warnings. {color} | | {color:black}{color} | {color:black} {color} | {color:black} 13m 54s{color} | {color:black} {color} | \\ \\ || Subsystem || Report/Notes || | Optional Tests | asflicense javac javadoc findbugs checkstyle compile | | uname | Linux hiveptest-server-upstream 3.16.0-4-amd64 #1 SMP Debian 3.16.36-1+deb8u1 (2016-09-03) x86_64 GNU/Linux | | Build tool | maven | | Personality | /data/hiveptest/working/yetus_PreCommit-HIVE-Build-9369/dev-support/hive-personality.sh | | git revision | master / 8d2a23a | | Default Java | 1.8.0_111 | | checkstyle | http://104.198.109.242/logs//PreCommit-HIVE-Build-9369/yetus/diff-checkstyle-ql.txt | | asflicense | http://104.198.109.242/logs//PreCommit-HIVE-Build-9369/yetus/patch-asflicense-problems.txt | | modules | C: itests ql U: . | | Console output | http://104.198.109.242/logs//PreCommit-HIVE-Build-9369/yetus.txt | | Powered by | Apache Yetus http://yetus.apache.org | This message was automatically generated. > 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, HIVE-17178.4.patch, HIVE-17178.5.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. -- This message was sent by Atlassian JIRA (v7.6.3#76005)