iindyk commented on a change in pull request #15271:
URL: https://github.com/apache/beam/pull/15271#discussion_r683791140
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File path: sdks/python/apache_beam/transforms/combiners.py
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@@ -616,10 +621,23 @@ def create_accumulator(self, *args, **kwargs):
return [c.create_accumulator(*args, **kwargs) for c in self._combiners]
def merge_accumulators(self, accumulators, *args, **kwargs):
- return [
- c.merge_accumulators(a, *args, **kwargs) for c,
- a in zip(self._combiners, zip(*accumulators))
- ]
+ # Make sure that `accumulators` is an iterator (so that the position is
+ # remembered).
+ accumulators = iter(accumulators)
+ result = next(accumulators)
+ while True:
+ # Load accumulators into memory and merge in batches to decrease peak
+ # memory usage.
+ accumulators_batch = list(
Review comment:
You mean the # of packed accumulators (i.e. tupled CombineFns) ?
Yes, ideally, it's a function of # of packed accumulators and their sizes,
but since we don't know their sizes we wouldn't be able to derive a meaningful
estimate for the batch size given just the # of packed accumulators.
It might still make sense to have default have a ~ reverse linear dependency
on the # of packed accumulators though, but I'm not certain how to come up with
a magic number, e.g. `merge_accumulators_batch_size` = max(100, 10000/# of
combiners in a tuple). WDYT?
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