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https://issues.apache.org/jira/browse/SPARK-13634?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15381169#comment-15381169
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Sean Owen commented on SPARK-13634:
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Go ahead, though in general I think it's pretty implicit that you can't
serialize context-like objects anywhere. This may in fact be just a hack, and
you need to redesign your code so that objects that are sent around do not
capture a context object to begin with. Your use case is not normal shell
usage; you're writing a custom framework. You can suggest doc changes (in a
PR); just consider what is quite specific to your usage vs what is likely
widely applicable enough to go in the docs.
> Assigning spark context to variable results in serialization error
> ------------------------------------------------------------------
>
> Key: SPARK-13634
> URL: https://issues.apache.org/jira/browse/SPARK-13634
> Project: Spark
> Issue Type: Bug
> Components: Spark Shell
> Reporter: Rahul Palamuttam
> Priority: Minor
>
> The following lines of code cause a task serialization error when executed in
> the spark-shell.
> Note that the error does not occur when submitting the code as a batch job -
> via spark-submit.
> val temp = 10
> val newSC = sc
> val new RDD = newSC.parallelize(0 to 100).map(p => p + temp)
> For some reason when temp is being pulled in to the referencing environment
> of the closure, so is the SparkContext.
> We originally hit this issue in the SciSpark project, when referencing a
> string variable inside of a lambda expression in RDD.map(...)
> Any insight into how this could be resolved would be appreciated.
> While the above code is trivial, SciSpark uses a wrapper around the
> SparkContext to read from various file formats. We want to keep this class
> structure and also use it in notebook and shell environments.
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