Implement Cross-Bundle BatchElements #29175
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@@ Coverage Diff @@
## master #29175 +/- ##
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- Coverage 38.38% 38.31% -0.08%
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Files 686 688 +2
Lines 101640 101907 +267
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+ Hits 39018 39041 +23
- Misses 61042 61286 +244
Partials 1580 1580
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jrmccluskey
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R: @damccorm |
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| def expand(self, pcoll): | ||
| if getattr(pcoll.pipeline.runner, 'is_streaming', False): | ||
| raise NotImplementedError("Requires stateful processing (BEAM-2687)") | ||
| elif self._max_batch_dur is not None: | ||
| coder = coders.registry.get_coder(pcoll) | ||
| return pcoll | WithKeys(0) | ParDo( |
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Non-blocking for this PR, but something we may want to consider; rather than using a single fixed key, does it make sense to try to have a single key per worker somehow? (one way to do this would be using multi_process_shared.py)
That way we're still batching per machine in a parallelizable way, but we get stateful batching across bundles.
The current implementation is likely still useful for many use cases where batching is not the expensive part (e.g. RunInference) or there are few workers.
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At one point I suggested keying with worker IDs, it may be worth coming back to that idea
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Oh I missed that (or forgot), hopefully I wasn't against it initially?
Regardless, I like having this as our first pass, we can see how it performs and go from there
Implements a stateful version of
BatchElementsthat works across bundles, allowing for streaming pipelines that can batch elements in a dynamic fashion.Thank you for your contribution! Follow this checklist to help us incorporate your contribution quickly and easily:
addresses #123), if applicable. This will automatically add a link to the pull request in the issue. If you would like the issue to automatically close on merging the pull request, commentfixes #<ISSUE NUMBER>instead.CHANGES.mdwith noteworthy changes.See the Contributor Guide for more tips on how to make review process smoother.
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