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https://issues.apache.org/jira/browse/SPARK-7043?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14527683#comment-14527683
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Frederick Reiss commented on SPARK-7043:
----------------------------------------
Both issues appear to have the same root cause: The interpreter's rewrites
create a class with a transient reference to the Spark context, and Kryo
creates a second context during deserialization.
> KryoSerializer cannot be used with REPL to interpret code in which case class
> definition and its shipping are in the same line
> ------------------------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-7043
> URL: https://issues.apache.org/jira/browse/SPARK-7043
> Project: Spark
> Issue Type: Bug
> Components: Spark Shell
> Affects Versions: 1.3.1
> Environment: Ubuntu 14.04, no hadoop
> Reporter: Peng Cheng
> Priority: Minor
> Labels: classloader, kryo
> Original Estimate: 48h
> Remaining Estimate: 48h
>
> When deploying Spark-shell with
> "spark.serializer=org.apache.spark.serializer.KryoSerializer" option.
> Spark-shell cannot execute the following code (in 1 line):
> case class Foo(i: Int);val ret = sc.parallelize((1 to 100).map(Foo),
> 10).collect()
> This problem won't exist for either JavaSerializer or code splitted into 2
> lines. The only possible explanation is that KryoSerializer is using a
> ClassLoader that is not registered as an subsidiary ClassLoader of the one in
> REPL.
> A "dirty" fix would be just breaking input by semicolon, but its better to
> fix the ClassLoader to avoid other liabilities.
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