[jira] [Updated] (FLINK-30533) SourceOperator#emitNext() should push records to DataOutput in a while loop

["Dong Lin (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/FLINK-30533?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Dong Lin updated FLINK-30533:
-----------------------------
    Summary: SourceOperator#emitNext() should push records to DataOutput in a while loop  (was: IteratorSourceReaderBase#pollNext() should push records to ReaderOutput in a while loop)

> SourceOperator#emitNext() should push records to DataOutput in a while loop
> ---------------------------------------------------------------------------
>
>                 Key: FLINK-30533
>                 URL: https://issues.apache.org/jira/browse/FLINK-30533
>             Project: Flink
>          Issue Type: Sub-task
>          Components: Runtime / Task
>            Reporter: Dong Lin
>            Assignee: Dong Lin
>            Priority: Major
>              Labels: pull-request-available
>
> Currently, each invocation of IteratorSourceReaderBase#pollNext() push at most one record to the given ReaderOutput. This unnecessarily increases the average Java call stack depth needed to produce an element.
>  
> Take the following program as an example. For each element produced by this program, Flink runtime needs to include in the call stack these 4 function calls:
>  * StreamTask#processInput()
>  * StreamOneInputProcessor#processInput()
>  * StreamTaskSourceInput#emitNext()
>  * SourceOperator#emitNext()
> {code:java}
> DataStream<Long> stream = env.fromSequence(1, 1000000000L)
> .map(x -> x)
> .addSink(new DiscardingSink<>());
> {code}
>  
> In comparison, SourceReaderBase#pollNext() is already using a while loop so that each invocation of this method could push as many records to the given ReaderOutput as possible.
>  
> This ticket proposes to update IteratorSourceReaderBase#pollNext() to push records to ReaderOutput in a while loop. It improves performance for programs that IteratorSourceReaderBase (e.g. env.fromSequence) by removing an average of 3 function from the call stack needed to produce a record.
>  
> Here are the benchmark results by running the above program with parallelism=1 and 5 runs per setup.
>  * Prior to the proposed change, the average execution time is 33.3 sec with std=0.9 sec.
>  * After the proposed change, the average execution time is 46.1 sec with std=5.1 sec.
>  * The proposed change increases throughput by 38.4%.
>  



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