[jira] [Commented] (HIVE-8610) Compile time skew join optimization doesn't work with auto map join

["Rui Li (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/HIVE-8610?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14186853#comment-14186853 ] 

Rui Li commented on HIVE-8610:
------------------------------

Hi [~xuefuz], do I have to add something to {{testconfiguration.properties}} to make hive automatically run the new tests for MR?

> Compile time skew join optimization doesn't work with auto map join
> -------------------------------------------------------------------
>
>                 Key: HIVE-8610
>                 URL: https://issues.apache.org/jira/browse/HIVE-8610
>             Project: Hive
>          Issue Type: Bug
>            Reporter: Rui Li
>            Assignee: Rui Li
>         Attachments: HIVE-8610.1.patch
>
>
> NPE is thrown if both {{hive.optimize.skewjoin.compiletime}} and {{hive.auto.convert.join}} are enabled:
> {code}
> java.lang.NullPointerException
> 	at org.apache.hadoop.hive.ql.optimizer.MapJoinProcessor.convertMapJoin(MapJoinProcessor.java:329)
> 	at org.apache.hadoop.hive.ql.optimizer.MapJoinProcessor.genMapJoinOpAndLocalWork(MapJoinProcessor.java:236)
> 	at org.apache.hadoop.hive.ql.optimizer.physical.CommonJoinTaskDispatcher.convertTaskToMapJoinTask(CommonJoinTaskDispatcher.java:181)
> 	at org.apache.hadoop.hive.ql.optimizer.physical.CommonJoinTaskDispatcher.processCurrentTask(CommonJoinTaskDispatcher.java:463)
> 	at org.apache.hadoop.hive.ql.optimizer.physical.AbstractJoinTaskDispatcher.dispatch(AbstractJoinTaskDispatcher.java:182)
> 	at org.apache.hadoop.hive.ql.lib.TaskGraphWalker.dispatch(TaskGraphWalker.java:111)
> 	at org.apache.hadoop.hive.ql.lib.TaskGraphWalker.walk(TaskGraphWalker.java:194)
> 	at org.apache.hadoop.hive.ql.lib.TaskGraphWalker.startWalking(TaskGraphWalker.java:139)
> 	at org.apache.hadoop.hive.ql.optimizer.physical.CommonJoinResolver.resolve(CommonJoinResolver.java:79)
> 	at org.apache.hadoop.hive.ql.optimizer.physical.PhysicalOptimizer.optimize(PhysicalOptimizer.java:107)
> 	at org.apache.hadoop.hive.ql.parse.MapReduceCompiler.optimizeTaskPlan(MapReduceCompiler.java:275)
> 	at org.apache.hadoop.hive.ql.parse.TaskCompiler.compile(TaskCompiler.java:223)
> 	at org.apache.hadoop.hive.ql.parse.SemanticAnalyzer.analyzeInternal(SemanticAnalyzer.java:10028)
> 	at org.apache.hadoop.hive.ql.parse.BaseSemanticAnalyzer.analyze(BaseSemanticAnalyzer.java:221)
> 	at org.apache.hadoop.hive.ql.parse.ExplainSemanticAnalyzer.analyzeInternal(ExplainSemanticAnalyzer.java:74)
> 	at org.apache.hadoop.hive.ql.parse.BaseSemanticAnalyzer.analyze(BaseSemanticAnalyzer.java:221)
> 	at org.apache.hadoop.hive.ql.Driver.compile(Driver.java:415)
> 	at org.apache.hadoop.hive.ql.Driver.compile(Driver.java:303)
> 	at org.apache.hadoop.hive.ql.Driver.compileInternal(Driver.java:1068)
> 	at org.apache.hadoop.hive.ql.Driver.runInternal(Driver.java:1130)
> 	at org.apache.hadoop.hive.ql.Driver.run(Driver.java:1005)
> 	at org.apache.hadoop.hive.ql.Driver.run(Driver.java:995)
> 	at org.apache.hadoop.hive.cli.CliDriver.processLocalCmd(CliDriver.java:246)
> 	at org.apache.hadoop.hive.cli.CliDriver.processCmd(CliDriver.java:198)
> 	at org.apache.hadoop.hive.cli.CliDriver.processLine(CliDriver.java:408)
> 	at org.apache.hadoop.hive.cli.CliDriver.executeDriver(CliDriver.java:781)
> 	at org.apache.hadoop.hive.cli.CliDriver.run(CliDriver.java:675)
> 	at org.apache.hadoop.hive.cli.CliDriver.main(CliDriver.java:614)
> 	at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> 	at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
> 	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> 	at java.lang.reflect.Method.invoke(Method.java:606)
> 	at org.apache.hadoop.util.RunJar.main(RunJar.java:212)
> {code}
> A simple way to reproduce this issue is to add {{set hive.auto.convert.join=true}} to one of the skew join qfile, e.g. {{skewjoinopt2.q}}.
> While reduce side join can produce correct results, we kind of lost the point of skew join optimization - join skewed data via a map join to avoid one reducer getting too much records.



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