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https://issues.apache.org/jira/browse/SPARK-22163?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Steve Loughran updated SPARK-22163:
-----------------------------------
Priority: Major (was: Critical)
> Design Issue of Spark Streaming that Causes Random Run-time Exception
> ---------------------------------------------------------------------
>
> Key: SPARK-22163
> URL: https://issues.apache.org/jira/browse/SPARK-22163
> Project: Spark
> Issue Type: Bug
> Components: DStreams, Structured Streaming
> Affects Versions: 2.2.0
> Environment: Spark Streaming
> Kafka
> Linux
> Reporter: Michael N
>
> The application objects can contain List and can be modified dynamically as
> well. However, Spark Streaming framework asynchronously serializes the
> application's objects as the application runs. Therefore, it causes random
> run-time exception on the List when Spark Streaming framework happens to
> serializes the application's objects while the application modifies a List in
> its own object.
> In fact, there are multiple bugs reported about
> Caused by: java.util.ConcurrentModificationException
> at java.util.ArrayList.writeObject
> that are permutation of the same root cause. So the design issue of Spark
> streaming framework is that it should do this serialization asynchronously.
> Instead, it should either
> 1. do this serialization synchronously. This is preferred to eliminate the
> issue completely. Or
> 2. Allow it to be configured per application whether to do this serialization
> synchronously or asynchronously, depending on the nature of each application.
> Also, Spark documentation should describe the conditions that trigger Spark
> to do this type of serialization asynchronously, so the applications can work
> around them until the fix is provided.
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