[jira] [Work logged] (BEAM-9346) TFRecordIO inefficient read from sideinput causing pipeline to be slow

["ASF GitHub Bot (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/BEAM-9346?focusedWorklogId=419768&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-419768 ]

ASF GitHub Bot logged work on BEAM-9346:
----------------------------------------

                Author: ASF GitHub Bot
            Created on: 09/Apr/20 21:08
            Start Date: 09/Apr/20 21:08
    Worklog Time Spent: 10m 
      Work Description: chamikaramj commented on pull request #11122: [BEAM-9346] Improve the efficiency of TFRecordIO
URL: https://github.com/apache/beam/pull/11122#discussion_r406478334
 
 

 ##########
 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:
   What's the verdict here ? I suggest we revert this and introduce as an optional change since this is a potential regression for Dataflow runner.
 
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Issue Time Tracking
-------------------

    Worklog Id:     (was: 419768)
    Time Spent: 3h 40m  (was: 3.5h)

> 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 40m
>  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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