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Posted to issues@spark.apache.org by "Charles Allen (JIRA)" <ji...@apache.org> on 2017/02/22 18:46:44 UTC
[jira] [Comment Edited] (SPARK-19698) Race condition in stale
attempt task completion vs current attempt task completion when task is
doing persistent state changes
[ https://issues.apache.org/jira/browse/SPARK-19698?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15878959#comment-15878959 ]
Charles Allen edited comment on SPARK-19698 at 2/22/17 6:46 PM:
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I *think* this is due to the driver not having the concept of a "critical section" for code being executed, meaning that you can't declare a portion of the code being run as "I'm in a non-atomic or critical command region, please let me finish"
was (Author: drcrallen):
I *think* this is due to the driver not having the concept of a "critical section" for code being executed, meaning that you can't declare a portion of the code being run as "I'm in a non-idempotent command region, please let me finish"
> Race condition in stale attempt task completion vs current attempt task completion when task is doing persistent state changes
> ------------------------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-19698
> URL: https://issues.apache.org/jira/browse/SPARK-19698
> Project: Spark
> Issue Type: Bug
> Components: Mesos, Spark Core
> Affects Versions: 2.0.0
> Reporter: Charles Allen
>
> We have encountered a strange scenario in our production environment. Below is the best guess we have right now as to what's going on.
> Potentially, the final stage of a job has a failure in one of the tasks (such as OOME on the executor) which can cause tasks for that stage to be relaunched in a second attempt.
> https://github.com/apache/spark/blob/v2.1.0/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala#L1155
> keeps track of which tasks have been completed, but does NOT keep track of which attempt those tasks were completed in. As such, we have encountered a scenario where a particular task gets executed twice in different stage attempts, and the DAGScheduler does not consider if the second attempt is still running. This means if the first task attempt succeeded, the second attempt can be cancelled part-way through its run cycle if all other tasks (including the prior failed) are completed successfully.
> What this means is that if a task is manipulating some state somewhere (for example: a upload-to-temporary-file-location, then delete-then-move on an underlying s3n storage implementation) the driver can improperly shutdown the running (2nd attempt) task between state manipulations, leaving the persistent state in a bad state since the 2nd attempt never got to complete its manipulations, and was terminated prematurely at some arbitrary point in its state change logic (ex: finished the delete but not the move).
> This is using the mesos coarse grained executor. It is unclear if this behavior is limited to the mesos coarse grained executor or not.
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