ntopousis commented on code in PR #39372:
URL: https://github.com/apache/beam/pull/39372#discussion_r3660556057
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sdks/java/core/src/main/java/org/apache/beam/sdk/io/WriteFiles.java:
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@@ -553,29 +556,53 @@ public PCollection<List<ResultT>>
expand(PCollection<ResultT> input) {
// Reshuffle one more time to stabilize the contents of the bundle
lists to finalize.
.apply(Reshuffle.viaRandomKey());
} else {
- // Pass results via a side input rather than reshuffle, because we
need to get an empty
- // iterable to finalize if there are no results.
- return input
- .getPipeline()
- .apply(
- "AsPossiblyEmptyList",
- Reify.viewInGlobalWindow(
- // Insert a reshuffle before taking the view to
consolidate the (typically)
- // one-output-per-bundle writes.
- // This avoids producing a huge number of tiny files in
the case that side
- // inputs are materialized to disk bundle-by-bundle.
- input.apply("Consolidate",
Reshuffle.viaRandomKey()).apply(View.asIterable()),
Review Comment:
Thank you for the comment. What's your recommendation for benchmarking?
Internally, Block has large enough dataflow jobs to benchmark, but obviously,
the details of the benchmark wouldn't be publicly verifiable. Are there known,
open datasets/jobs that contributors/maintainers use for benchmarking?
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