Github user JoshRosen commented on a diff in the pull request:
https://github.com/apache/spark/pull/1977#discussion_r27998013
--- Diff: python/pyspark/rdd.py ---
@@ -1755,21 +1753,33 @@ 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 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 --
Is this still true?
[Upthread](https://github.com/apache/spark/pull/1977#issuecomment-56004283),
you mentioned that this can now be iterated multiple times, so we should
probably update this comment. It would also be nice to add a unit test to
illustrate that the calling `len(values)` then reading the values will work,
even if it's inefficient (you might have already done this in tests, though; I
haven't checked).
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