Github user mateiz commented on a diff in the pull request:
https://github.com/apache/spark/pull/1460#discussion_r15072948
--- Diff: python/pyspark/rdd.py ---
@@ -1247,15 +1366,12 @@ def combineLocally(iterator):
return combiners.iteritems()
locally_combined = self.mapPartitions(combineLocally)
shuffled = locally_combined.partitionBy(numPartitions)
-
+
+ executorMemory = self.ctx._jsc.sc().executorMemory()
def _mergeCombiners(iterator):
- combiners = {}
- for (k, v) in iterator:
- if k not in combiners:
- combiners[k] = v
- else:
- combiners[k] = mergeCombiners(combiners[k], v)
- return combiners.iteritems()
+ merger = Merger(mergeCombiners, executorMemory * 0.7)
--- End diff --
We probably want to use the same memory as the Java append only map, which
is spark.shuffle.memoryFraction * executorMemory. Check how that gets created
in ExternalAppendOnlyMap
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