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Posted to issues@spark.apache.org by "Mridul Muralidharan (Jira)" <ji...@apache.org> on 2022/08/11 17:19:00 UTC
[jira] [Resolved] (SPARK-39955) Improve LaunchTask process to avoid Stage failures caused by fail-to-send LaunchTask messages
[ https://issues.apache.org/jira/browse/SPARK-39955?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Mridul Muralidharan resolved SPARK-39955.
-----------------------------------------
Fix Version/s: 3.4.0
Resolution: Fixed
Issue resolved by pull request 37384
[https://github.com/apache/spark/pull/37384]
> Improve LaunchTask process to avoid Stage failures caused by fail-to-send LaunchTask messages
> ---------------------------------------------------------------------------------------------
>
> Key: SPARK-39955
> URL: https://issues.apache.org/jira/browse/SPARK-39955
> Project: Spark
> Issue Type: Improvement
> Components: Spark Core
> Affects Versions: 3.4.0
> Reporter: Kai-Hsun Chen
> Priority: Major
> Fix For: 3.4.0
>
>
> There are two possible reasons, including Network Failure and Task Failure, to make RPC failures.
> (1) Task Failure: The network is good, but the task causes the executor's JVM crash. Hence, RPC fails.
> (2) Network Failure: The executor works well, but the network between Driver and Executor is broken. Hence, RPC fails.
> We should handle these two different kinds of failure in different ways. First, if the failure is Task Failure, we should increment the variable `{{{}numFailures`{}}}. If the value of {{`numFailures`}} is larger than a threshold, Spark will label the job failed. Second, if the failure is Network Failure, we will not increment the variable `{{{}numFailures`{}}}. We will just assign the task to a new executor. Hence, the job will not be recognized as failed due to Network Failure.
> However, currently, Spark recognizes every RPC failure as Task Failure. Hence, it will cause extra Spark job failures.
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