Details
Major Description
PySpark fails to deserialize double-zipped RDDs. For example, the following example used to work in Spark 2.0.2:
>>> a = sc.parallelize('aaa') >>> b = sc.parallelize('bbb') >>> c = sc.parallelize('ccc') >>> a_bc = a.zip( b.zip(c) ) >>> a_bc.collect() [('a', ('b', 'c')), ('a', ('b', 'c')), ('a', ('b', 'c'))]
But in Spark >=2.1.0, it fails (regardless of Python 2 vs 3):
>>> a_bc.collect() Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/workspace/spark-2.2.0-bin-hadoop2.7/python/pyspark/rdd.py", line 810, in collect return list(_load_from_socket(port, self._jrdd_deserializer)) File "/workspace/spark-2.2.0-bin-hadoop2.7/python/pyspark/serializers.py", line 329, in _load_stream_without_unbatching if len(key_batch) != len(val_batch): TypeError: object of type 'itertools.izip' has no len()
As you can see, the error seems to be caused by a check in the PairDeserializer class:
if len(key_batch) != len(val_batch): raise ValueError("Can not deserialize PairRDD with different number of items" " in batches: (%d, %d)" % (len(key_batch), len(val_batch)))
If that check is removed, then the example above works without error. Can the check simply be removed?
