[jira] [Commented] (SPARK-19644) Memory leak in Spark Streaming

["Sean Owen (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-19644?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15871436#comment-15871436 ] 

Sean Owen commented on SPARK-19644:
-----------------------------------

What you have described so far is not a memory leak in Spark. It's normal for the heap to grow unless it has reason to even garbage collect. You're not evidently running out of memory. You're talking about a heap change of 1.1 to 1.3MB, which is trivial (is this a typo?). I'd close this unless you have a clearer case.

> Memory leak in Spark Streaming
> ------------------------------
>
>                 Key: SPARK-19644
>                 URL: https://issues.apache.org/jira/browse/SPARK-19644
>             Project: Spark
>          Issue Type: Bug
>          Components: DStreams
>    Affects Versions: 2.0.2
>         Environment: 3 AWS EC2 c3.xLarge
> Number of cores - 3
> Number of executors 3 
> Memory to each executor 2GB
>            Reporter: Deenbandhu Agarwal
>            Priority: Critical
>              Labels: memory_leak, performance
>         Attachments: heapdump.png
>
>
> I am using streaming on the production for some aggregation and fetching data from cassandra and saving data back to cassandra. 
> I see a gradual increase in old generation heap capacity from 1161216 Bytes to 1397760 Bytes over a period of six hours.
> After 50 hours of processing instances of class scala.collection.immutable.$colon$colon incresed to 12,811,793 which is a huge number. 
> I think this is a clear case of memory leak



--
This message was sent by Atlassian JIRA
(v6.3.15#6346)

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