[jira] [Updated] (FLINK-14346) Performance issue with StringSerializer

["Gary Yao (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/FLINK-14346?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Gary Yao updated FLINK-14346:
-----------------------------
    Release Note:   (was: Improved string serialisation and deserialisation performance.)

> Performance issue with StringSerializer
> ---------------------------------------
>
>                 Key: FLINK-14346
>                 URL: https://issues.apache.org/jira/browse/FLINK-14346
>             Project: Flink
>          Issue Type: Improvement
>          Components: API / Type Serialization System, Benchmarks
>    Affects Versions: 1.9.0, 1.9.1, 1.10.0
>         Environment: Tested on Flink 1.10.0-SNAPSHOT-20191129-034045-139, adoptopenjdk 8u222.
>            Reporter: Roman Grebennikov
>            Assignee: Roman Grebennikov
>            Priority: Major
>              Labels: performance, pull-request-available
>             Fix For: 1.10.0
>
>          Time Spent: 20m
>  Remaining Estimate: 0h
>
> While doing a performance profiling for our Flink state-heavy streaming job, we found that quite  a significant amount of CPU time is spent inside StringSerializer writing data to the underlying byte buffer. The hottest part of the code is the StringValue.writeString function. And replacing the default StringSerializer with the custom one (to just play with a baseline), which is just calling DataOutput.writeUTF/readUTF surprisingly yielded to almost 2x speedup for string serialization.
> As writeUTF and writeString have incompatible wire formats, replacing latter with former is not a good idea in general as it may break checkpoint/savepoint compatibility.
> We also did an early performance analysis of the root cause of this performance issue, and the main reason of JDK's writeUTF being faster is that it's code is not writing directly to output stream byte-by-byte, but instead creating an underlying temporary byte buffer. This yields to a HotSpot almost perfectly unrolling the main loop, which results in much better data parallelism.
> I've tried to port the ideas from the JVM's implementation of writeUTF back to StringValue.writeString, and my current result is nice, having quite significant speedup compared to the current implementation:
> {{[info] Benchmark Mode Cnt Score Error Units}}
> {{[info] StringSerializerBenchmark.measureJDK avgt 30 82.871 ± 1.293 ns/op}}
> {{[info] StringSerializerBenchmark.measureNew avgt 30 94.004 ± 1.491 ns/op}}
> {{[info] StringSerializerBenchmark.measureOld avgt 30 156.905 ± 3.596 ns/op}}
>  
> {{Where measureJDK is the JDK's writeUTF asa baseline, measureOld is the current upstream implementation in Flink, and the measureNew is the improved one. }}
>  
> {{The code for the benchmark (and the improved version of the serializer) is here: [https://github.com/shuttie/flink-string-serializer]}}
>  
> {{Next steps:}}
>  # {{More benchmarks for non-ascii strings.}}
>  # {{Benchmarks for long strings.}}
>  # {{Benchmarks for deserialization.}}
>  # {{Tests for old-new wire format compatibility.}}
>  # {{PR to the Flink codebase.}}
> {{Is there an interest for this kind of performance improvement?}}



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