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https://issues.apache.org/jira/browse/SPARK-10544?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14739492#comment-14739492
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Doug Bateman commented on SPARK-10544:
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This also fails in Spark 1.5 pyspark....
sc.parallelize(["the red", "Fox Runs", "FAST"]).map(str.lower).count()
Basically it can't pickle the str.lower function unless it's wrapped in a
lambda.
Same root issue... can't pickle builtin types.
> Serialization of Python namedtuple subclasses in functions / closures is
> broken
> -------------------------------------------------------------------------------
>
> Key: SPARK-10544
> URL: https://issues.apache.org/jira/browse/SPARK-10544
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 1.5.0
> Reporter: Josh Rosen
> Priority: Blocker
>
> The following example works on Spark 1.4.1 but not in 1.5:
> {code}
> from collections import namedtuple
> Person = namedtuple("Person", "id firstName lastName")
> rdd = sc.parallelize([1]).map(lambda x: Person(1, "Jon", "Doe"))
> rdd.count()
> {code}
> In 1.5, this gives an "AttributeError: 'builtin_function_or_method' object
> has no attribute '__code__'" error.
> Digging a bit deeper, it seems that the problem is the serialization of the
> {{Person}} class itself, since serializing _instances_ of the class in the
> closure seems to work properly:
> {code}
> from collections import namedtuple
> Person = namedtuple("Person", "id firstName lastName")
> jon = Person(1, "Jon", "Doe")
> rdd = sc.parallelize([1]).map(lambda x: jon)
> rdd.count()
> {code}
> It looks like PySpark has unit tests for serializing individual namedtuples
> with cloudpickle.dumps and for serializing RDDs of namedtuples, but I don't
> think that we have any tests for namedtuple classes in closures.
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