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https://issues.apache.org/jira/browse/SPARK-22674?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16276390#comment-16276390
]
Hyukjin Kwon commented on SPARK-22674:
--------------------------------------
Not really. Regular pickle can pickle it but is unable to unpickle it without
explicit class declaration:
{code}
import pickle
from collections import namedtuple
Point = namedtuple("Point", "x y")
class PointSubclass(Point):
def sum(self):
return self.x + self.y
w = open("foo", "w")
w.write(pickle.dumps(PointSubclass(1, 2)))
exit(0)
pickle.loads(open("foo").read())
{code}
Open {{python}} again:
{code}
import pickle
pickle.loads(open("foo").read())
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/.../2.7/lib/python2.7/pickle.py", line 1382, in loads
return Unpickler(file).load()
File "/.../2.7/lib/python2.7/pickle.py", line 858, in load
dispatch[key](self)
File "/.../2.7/lib/python2.7/pickle.py", line 1090, in load_global
klass = self.find_class(module, name)
File "/.../2.7/lib/python2.7/pickle.py", line 1126, in find_class
klass = getattr(mod, name)
AttributeError: 'module' object has no attribute 'PointSubclass'
{code}
After the fix in cloudpickle:
{code}
import cloudpickle
from collections import namedtuple
Point = namedtuple("Point", "x y")
class PointSubclass(Point):
def sum(self):
return self.x + self.y
w = open("foo", "w")
w.write(cloudpickle.dumps(PointSubclass(1, 2)))
exit(0)
{code}
Open {{python}} again:
{code}
import pickle
pickle.loads(open("foo").read())
{code}
PySpark's cloudpickle fixed it in a hijacking way to avoid this problem first
before cloudpickle fixes it. After that, cloudpickle introduced the fix I
pointed out.
> 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
>
> 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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