[
https://issues.apache.org/jira/browse/FLINK-14346?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16985077#comment-16985077
]
Roman Grebennikov commented on FLINK-14346:
-------------------------------------------
PR for the flink-benchmarks:
[https://github.com/dataArtisans/flink-benchmarks/pull/36]
Results are quite nice, +20% gain for string-heavy jobs:
{noformat}
Original:
Benchmark Mode Cnt Score
Error Units
SerializationFrameworkMiniBenchmarks.serializerHeavyPojo thrpt 30 100.689 ±
1.716 ops/ms
SerializationFrameworkMiniBenchmarks.serializerKryo thrpt 30 211.890 ±
5.048 ops/ms
SerializationFrameworkMiniBenchmarks.serializerPojo thrpt 30 473.830 ±
11.037 ops/ms
SerializationFrameworkMiniBenchmarks.serializerRow thrpt 30 549.780 ±
11.578 ops/ms
SerializationFrameworkMiniBenchmarks.serializerTuple thrpt 30 587.982 ±
8.941 ops/ms
Improved:
Benchmark Mode Cnt Score
Error Units
SerializationFrameworkMiniBenchmarks.serializerHeavyPojo thrpt 30 121.078 ±
2.657 ops/ms
SerializationFrameworkMiniBenchmarks.serializerKryo thrpt 30 220.956 ±
7.624 ops/ms
SerializationFrameworkMiniBenchmarks.serializerPojo thrpt 30 445.025 ±
6.894 ops/ms
SerializationFrameworkMiniBenchmarks.serializerRow thrpt 30 521.074 ±
9.481 ops/ms
SerializationFrameworkMiniBenchmarks.serializerTuple thrpt 30 545.966 ±
8.708 ops/ms{noformat}
> 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, 1.10.0, 1.9.1
> Environment: Tested on Flink 1.10.0-SNAPSHOT-20191129-034045-139,
> adoptopenjdk 8u222.
> Reporter: Roman Grebennikov
> Priority: Major
> Labels: performance, pull-request-available
> Time Spent: 10m
> 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?}}
--
This message was sent by Atlassian Jira
(v8.3.4#803005)
