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