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https://issues.apache.org/jira/browse/SPARK-19698?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15881688#comment-15881688
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Kay Ousterhout commented on SPARK-19698:
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My concern is that there are other cases in Spark where this issue could arise
(so Spark tasks need to be very careful about how they modify external state).
Here's another scenario:
- Attempt 0 of a task starts and takes a long time to run
- A second, speculative copy of the task is started (attempt 1)
- Attempt 0 finishes successfully, but attempt 1 is still running
- Attempt 1 gets partway through modifying the external state, but then gets
killed because of an OOM on the machine
- Attempt 1 won't get re-started, because a copy of the task already finished
successfully
This seems like it will have the same issue you mentioned in the JIRA, right?
> 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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