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https://issues.apache.org/jira/browse/BEAM-9346?focusedWorklogId=406723&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-406723
]
ASF GitHub Bot logged work on BEAM-9346:
----------------------------------------
Author: ASF GitHub Bot
Created on: 20/Mar/20 02:30
Start Date: 20/Mar/20 02:30
Worklog Time Spent: 10m
Work Description: lukecwik commented on pull request #11122: [BEAM-9346]
Improve the efficiency of TFRecordIO
URL: https://github.com/apache/beam/pull/11122#discussion_r395414286
##########
File path: sdks/java/core/src/main/java/org/apache/beam/sdk/io/WriteFiles.java
##########
@@ -410,13 +412,44 @@ private GatherResults(Coder<ResultT> resultCoder) {
} 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(Reify.viewInGlobalWindow(input.apply(View.asList()),
ListCoder.of(resultCoder)));
+ return input.apply("ToList", Combine.globally(new
ToListCombineFn<>()));
Review comment:
I believe this could be a regression based upon the above comment a few
lines higher then where the code was changed:
```
// Pass results via a side input rather than reshuffle, because we need to
get an empty
// iterable to finalize if there are no results.
```
The combine globally in the global window will produce a default output in
the global window but will throw an exception if used against non-global window
PCollections.
Performance wise this is likely an improvement overall since runners
typically do a better job with GBK then with side inputs. So we could keep this
change as an optimization in the global window case and keep the existing
behavior for non global windows.
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Issue Time Tracking
-------------------
Worklog Id: (was: 406723)
Time Spent: 3h (was: 2h 50m)
> TFRecordIO inefficient read from sideinput causing pipeline to be slow
> ----------------------------------------------------------------------
>
> Key: BEAM-9346
> URL: https://issues.apache.org/jira/browse/BEAM-9346
> Project: Beam
> Issue Type: Improvement
> Components: sdk-java-core
> Reporter: Ban Piao
> Assignee: Piotr Szuberski
> Priority: Major
> Labels: dataflow, easyfix, performance
> Fix For: Not applicable
>
> Time Spent: 3h
> Remaining Estimate: 0h
>
> In TFRecordIO, Reify.viewInGlobalWindow(input.apply(View.asList()),
> ListCoder.of(resultCoder)) is an inefficient way of reading large set of side
> input.
> Pipeline can be sped up significantly by combinging the PCollection<ResultT>
> to a single element PCollection<List<ResultT>>.
> Sample code:
>
> https://github.com/apache/beam/blob/master/sdks/java/core/src/main/java/org/apache/beam/sdk/io/WriteFiles.java#L412
> from
> ```
> return input
> .getPipeline()
> .apply(Reify.viewInGlobalWindow(input.apply(View.asList()),
> ListCoder.of(resultCoder)));
> ```
> to
> ```
> return input.apply("ToList", Combine.globally(new ToListCombineFn<>()));
> ```
> where ToListCombineFn is defined as
> ```
> public static class ToListCombineFn<ResultT> extends CombineFn<ResultT,
> List<ResultT>, List<ResultT>> {
> @Override
> public List<ResultT> createAccumulator() {
> return new ArrayList<>();
> }
> @Override
> public List<ResultT> addInput(List<ResultT> mutableAccumulator, ResultT
> input) {
> mutableAccumulator.add(input);
> return mutableAccumulator;
> }
> @Override
> public List<ResultT> mergeAccumulators(Iterable<List<ResultT>>
> accumulators) {
> Iterator<List<ResultT>> iter = accumulators.iterator();
> if (!iter.hasNext()) {
> return new ArrayList<>();
> }
> List<ResultT> merged = iter.next();
> while (iter.hasNext()) {
> merged.addAll(iter.next());
> }
> return merged;
> }
> @Override
> public List<ResultT> extractOutput(List<ResultT> accumulator) {
> return accumulator;
> }
> }
> ```
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