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https://issues.apache.org/jira/browse/SPARK-22674?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16398842#comment-16398842
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Jonas Amrich commented on SPARK-22674:
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[~lebedev] I completely agree, removing it is IMHO the cleanest solution.
I think namedtuples were originally used for representation of structured data
in RDDs - see -SPARK-2010- and -SPARK-1687- . This mechanism was then replaced
by the Row class in DataFrame API and it seems to me there is no use of it in
pyspark internals. However removing it would still be a BC break.
> PySpark breaks serialization of namedtuple subclasses
> -----------------------------------------------------
>
> Key: SPARK-22674
> URL: https://issues.apache.org/jira/browse/SPARK-22674
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 2.2.0
> Reporter: Jonas Amrich
> Priority: Major
>
> Pyspark monkey patches the namedtuple class to make it serializable, however
> this breaks serialization of its subclasses. With current implementation, any
> subclass will be serialized (and deserialized) as it's parent namedtuple.
> Consider this code, which will fail with {{AttributeError: 'Point' object has
> no attribute 'sum'}}:
> {code}
> from collections import namedtuple
> Point = namedtuple("Point", "x y")
> class PointSubclass(Point):
> def sum(self):
> return self.x + self.y
> rdd = spark.sparkContext.parallelize([[PointSubclass(1, 1)]])
> rdd.collect()[0][0].sum()
> {code}
> Moreover, as PySpark hijacks all namedtuples in the main module, importing
> pyspark breaks serialization of namedtuple subclasses even in code which is
> not related to spark / distributed execution. I don't see any clean solution
> to this; a possible workaround may be to limit serialization hack only to
> direct namedtuple subclasses like in
> https://github.com/JonasAmrich/spark/commit/f3efecee28243380ecf6657fe54e1a165c1b7204
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