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https://issues.apache.org/jira/browse/HIVE-8457?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14183172#comment-14183172
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Hive QA commented on HIVE-8457:
-------------------------------
{color:red}Overall{color}: -1 at least one tests failed
Here are the results of testing the latest attachment:
https://issues.apache.org/jira/secure/attachment/12676940/HIVE-8457.2-spark.patch
{color:red}ERROR:{color} -1 due to 2 failed/errored test(s), 6809 tests executed
*Failed tests:*
{noformat}
org.apache.hadoop.hive.cli.TestCliDriver.testCliDriver_sample_islocalmode_hook
org.apache.hadoop.hive.cli.TestCliDriver.testCliDriver_tez_smb_1
{noformat}
Test results:
http://ec2-174-129-184-35.compute-1.amazonaws.com/jenkins/job/PreCommit-HIVE-SPARK-Build/260/testReport
Console output:
http://ec2-174-129-184-35.compute-1.amazonaws.com/jenkins/job/PreCommit-HIVE-SPARK-Build/260/console
Test logs:
http://ec2-174-129-184-35.compute-1.amazonaws.com/logs/PreCommit-HIVE-SPARK-Build-260/
Messages:
{noformat}
Executing org.apache.hive.ptest.execution.PrepPhase
Executing org.apache.hive.ptest.execution.ExecutionPhase
Executing org.apache.hive.ptest.execution.ReportingPhase
Tests exited with: TestsFailedException: 2 tests failed
{noformat}
This message is automatically generated.
ATTACHMENT ID: 12676940 - PreCommit-HIVE-SPARK-Build
> MapOperator initialization fails when multiple Spark threads is enabled
> [Spark Branch]
> --------------------------------------------------------------------------------------
>
> Key: HIVE-8457
> URL: https://issues.apache.org/jira/browse/HIVE-8457
> Project: Hive
> Issue Type: Bug
> Components: Spark
> Reporter: Chao
> Assignee: Chao
> Attachments: HIVE-8457.1-spark.patch, HIVE-8457.2-spark.patch
>
>
> Currently, on the Spark branch, each thread it is bound with a thread-local
> IOContext, which gets initialized when we generates an input {{HadoopRDD}},
> and later used in {{MapOperator}}, {{FilterOperator}}, etc.
> And, given the introduction of HIVE-8118, we may have multiple downstream
> RDDs that share the same input {{HadoopRDD}}, and we would like to have the
> {{HadoopRDD}} to be cached, to avoid scanning the same table multiple times.
> A typical case would be like the following:
> {noformat}
> inputRDD inputRDD
> | |
> MT_11 MT_12
> | |
> RT_1 RT_2
> {noformat}
> Here, {{MT_11}} and {{MT_12}} are {{MapTran}} from a splitted {{MapWork}},
> and {{RT_1}} and {{RT_2}} are two {{ReduceTran}}. Note that, this example is
> simplified, as we may also have {{ShuffleTran}} between {{MapTran}} and
> {{ReduceTran}}.
> When multiple Spark threads are running, {{MT_11}} may be executed first, and
> it will ask for an iterator from the {{HadoopRDD}} will trigger the creation
> of the iterator, which in turn triggers the initialization of the
> {{IOContext}} associated with that particular thread.
> *Now, the problem is*: before {{MT_12}} starts executing, it will also ask
> for an iterator from the
> {{HadoopRDD}}, and since the RDD is already cached, instead of creating a new
> iterator, it will just fetch it from the cached result. However, *this will
> skip the initialization of the IOContext associated with this particular
> thread*. And, when {{MT_12}} starts executing, it will try to initialize the
> {{MapOperator}}, but since the {{IOContext}} is not initialized, this will
> fail miserably.
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