[ 
https://issues.apache.org/jira/browse/SPARK-3015?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Patrick Wendell updated SPARK-3015:
-----------------------------------

    Affects Version/s:     (was: 1.0.2)
                       1.1.0

> Removing broadcast in quick successions causes Akka timeout
> -----------------------------------------------------------
>
>                 Key: SPARK-3015
>                 URL: https://issues.apache.org/jira/browse/SPARK-3015
>             Project: Spark
>          Issue Type: Bug
>          Components: Spark Core
>    Affects Versions: 1.1.0
>         Environment: Standalone EC2 Spark shell
>            Reporter: Andrew Or
>            Assignee: Andrew Or
>            Priority: Blocker
>             Fix For: 1.1.0
>
>
> This issue is originally reported in SPARK-2916 in the context of MLLib, but 
> we were able to reproduce it using a simple Spark shell command:
> {code}
> (1 to 10000).foreach { i => sc.parallelize(1 to 1000, 48).sum }
> {code}
> We still do not have a full understanding of the issue, but we have gleaned 
> the following information so far. When the driver runs a GC, it attempts to 
> clean up all the broadcast blocks that go out of scope at once. This causes 
> the driver to send out many blocking RemoveBroadcast messages to the 
> executors, which in turn send out blocking UpdateBlockInfo messages back to 
> the driver. Both of these calls block until they receive the expected 
> responses. We suspect that the high frequency at which we send these blocking 
> messages is the cause of either dropped messages or internal deadlock 
> somewhere.
> Unfortunately, it is highly difficult to reproduce depending on the 
> environment. We have been able to reproduce it on a 6-node cluster in 
> us-west-2, but not in us-west-1, for instance.



--
This message was sent by Atlassian JIRA
(v6.2#6252)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org

Reply via email to