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From JoshRosen <>
Subject [GitHub] spark pull request: [SPARK-3074] [PySpark] support groupByKey() wi...
Date Wed, 17 Sep 2014 17:18:31 GMT
Github user JoshRosen commented on a diff in the pull request:
    --- Diff: python/pyspark/ ---
    @@ -1562,21 +1560,34 @@ def createZero():
             return self.combineByKey(lambda v: func(createZero(), v), func, func, numPartitions)
    +    def _can_spill(self):
    +        return self.ctx._conf.get("spark.shuffle.spill", "True").lower() == "true"
    +    def _memory_limit(self):
    +        return _parse_memory(self.ctx._conf.get("spark.python.worker.memory", "512m"))
         # TODO: support variant with custom partitioner
         def groupByKey(self, numPartitions=None):
             Group the values for each key in the RDD into a single sequence.
    -        Hash-partitions the resulting RDD with into numPartitions partitions.
    +        Hash-partitions the resulting RDD with into numPartitions
    +        partitions.
    +        The values in the resulting RDD is iterable object L{ResultIterable},
    +        they can be iterated only once. The `len(values)` will result in
    --- End diff --
    This is a change from the old behavior.  Based on our discussion, I guess that we only
return a ResultIterable in cases where we spill and still return a list in the non-spilling

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