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https://issues.apache.org/jira/browse/HIVE-18301?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16306218#comment-16306218
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Rui Li commented on HIVE-18301:
-------------------------------
I think SMB map join is one case where the "input file change" event is
necessary -- whenever the big table input file changes, SMBMapJoinOperator
needs to find corresponding input files for small tables in order to performa
bucketed join. Maybe we can identify all such cases and make sure MapInput
cache is disabled. For other cases, we can cache MapInput and just fix the NPE.
[~xuefuz], could you share your thoughts on this? Thanks.
> Investigate to enable MapInput cache in Hive on Spark
> -----------------------------------------------------
>
> Key: HIVE-18301
> URL: https://issues.apache.org/jira/browse/HIVE-18301
> Project: Hive
> Issue Type: Bug
> Reporter: liyunzhang
> Assignee: liyunzhang
>
> Before IOContext problem is found in MapTran when spark rdd cache is enabled
> in HIVE-8920.
> so we disabled rdd cache in MapTran at
> [SparkPlanGenerator|https://github.com/kellyzly/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/exec/spark/SparkPlanGenerator.java#L202].
> The problem is IOContext seems not initialized correctly in the spark yarn
> client/cluster mode and caused the exception like
> {code}
> Job aborted due to stage failure: Task 93 in stage 0.0 failed 4 times, most
> recent failure: Lost task 93.3 in stage 0.0 (TID 616, bdpe48):
> java.lang.RuntimeException: Error processing row:
> java.lang.NullPointerException
> at
> org.apache.hadoop.hive.ql.exec.spark.SparkMapRecordHandler.processRow(SparkMapRecordHandler.java:165)
> at
> org.apache.hadoop.hive.ql.exec.spark.HiveMapFunctionResultList.processNextRecord(HiveMapFunctionResultList.java:48)
> at
> org.apache.hadoop.hive.ql.exec.spark.HiveMapFunctionResultList.processNextRecord(HiveMapFunctionResultList.java:27)
> at
> org.apache.hadoop.hive.ql.exec.spark.HiveBaseFunctionResultList.hasNext(HiveBaseFunctionResultList.java:85)
> at
> scala.collection.convert.Wrappers$JIteratorWrapper.hasNext(Wrappers.scala:42)
> at
> org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:125)
> at
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:79)
> at
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:47)
> at org.apache.spark.scheduler.Task.run(Task.scala:85)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> at java.lang.Thread.run(Thread.java:745)
> Caused by: java.lang.NullPointerException
> at
> org.apache.hadoop.hive.ql.exec.AbstractMapOperator.getNominalPath(AbstractMapOperator.java:101)
> at
> org.apache.hadoop.hive.ql.exec.MapOperator.cleanUpInputFileChangedOp(MapOperator.java:516)
> at
> org.apache.hadoop.hive.ql.exec.Operator.cleanUpInputFileChanged(Operator.java:1187)
> at
> org.apache.hadoop.hive.ql.exec.MapOperator.process(MapOperator.java:546)
> at
> org.apache.hadoop.hive.ql.exec.spark.SparkMapRecordHandler.processRow(SparkMapRecordHandler.java:152)
> ... 12 more
> Driver stacktrace:
> {code}
> in yarn client/cluster mode, sometimes
> [ExecMapperContext#currentInputPath|https://github.com/kellyzly/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/exec/mr/ExecMapperContext.java#L109]
> is null when rdd cach is enabled.
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