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https://issues.apache.org/jira/browse/SPARK-13634?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15381236#comment-15381236
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Rahul Palamuttam commented on SPARK-13634:
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Understood and thank you for explaining.
I agree that it is pretty implicit that you can't serialize context-like
objects, but it's a little strange when the object gets pulled in without the
user even writing code that explicitly does so (in the shell). I agree with
your latter point as well, and will take that into consideration. It could just
be too specific to the use case.
> 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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