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https://issues.apache.org/jira/browse/BEAM-9566?focusedWorklogId=410293&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-410293
]
ASF GitHub Bot logged work on BEAM-9566:
----------------------------------------
Author: ASF GitHub Bot
Created on: 26/Mar/20 14:08
Start Date: 26/Mar/20 14:08
Worklog Time Spent: 10m
Work Description: mxm commented on pull request #11237: [BEAM-9566]
Mitigate performance issue for output timestamp watermark holds
URL: https://github.com/apache/beam/pull/11237
Benchmarks have shown that the minimum output timestamp computation over all
timers is very expensive because we have to iterate over all keys in the
state
backend. This is especially costly for RocksDB.
This change introduces a cache which stores and updates the timer output
timestamps such that the minimum can be retrieved efficiently.
Only at startup the cache is populated from the state backend. This should
give us roughly the same performance as before introducing output timestamps
for
timers.
The following have been run with RocksDB:
Nexmark Query 12 before:
```
Conf Runtime(sec) (Baseline) Events(/sec) (Baseline) Results
(Baseline)
0000 105.3 950.0 9039
0001 2.2 4466.3 196
```
Nexmark query 12 with this change:
```
Performance:
Conf Runtime(sec) (Baseline) Events(/sec) (Baseline) Results
(Baseline)
0000 6.0 16730.8 1919
0001 0.8 12391.6 196
```
For more details please see BEAM-9566.
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Issue Time Tracking
-------------------
Worklog Id: (was: 410293)
Remaining Estimate: 0h
Time Spent: 10m
> Performance regression of FlinkRunner stream mode due to watermark holds
> update
> -------------------------------------------------------------------------------
>
> Key: BEAM-9566
> URL: https://issues.apache.org/jira/browse/BEAM-9566
> Project: Beam
> Issue Type: Bug
> Components: runner-flink, testing-nexmark
> Affects Versions: 2.20.0
> Reporter: Bingfeng Xia
> Assignee: Maximilian Michels
> Priority: Critical
> Fix For: 2.20.0
>
> Time Spent: 10m
> Remaining Estimate: 0h
>
> Nexmark tests show that the throughput of FlinkRunner with Rocksdb state
> backend dropped by 50%~80% in Query 4/5/6/9/11. Some other queries also
> dropped but not as much as these queries. Affected queries contain Keyed
> State.
>
>
> Nexmark tests results. Tests have been run on the same machine and can be
> reproduced.
> - before regression:
> {code:java}
> Performance:
> Conf Runtime(sec) (Baseline) Events(/sec) (Baseline) Results
> (Baseline)
> 0000 3.8 26171.2 100000
> 0001 3.9 25967.3 92000
> 0002 1.9 53447.4 351
> 0003 2.8 35791.0 580
> 0004 2.5 4045.3 40
> 0005 9.6 10448.2 12
> 0006 1.2 8532.4 401
> 0007 4.0 25018.8 1
> 0008 2.9 34928.4 6000
> 0009 1.1 9066.2 298
> 0010 9.5 10564.1 2
> 0011 11.1 9005.0 1919
> 0012 4.5 22075.1 1919
> 0013 4.4 22547.9 92000
> 0014 9.7 10261.7 92000
> {code}
> - after regression:
> {code:java}
> Performance:
> Conf Runtime(sec) (Baseline) Events(/sec) (Baseline) Results
> (Baseline)
> 0000 4.5 22036.1 100000
> 0001 3.9 25839.8 92000
> 0002 2.3 43763.7 351
> 0003 3.5 28669.7 580
> 0004 3.6 2801.1 40
> 0005 22.6 4429.1 12
> 0006 2.5 3993.6 401
> 0007 7.5 13320.9 1
> 0008 2.7 36737.7 6000
> 0009 2.5 3930.8 298
> 0010 16.2 6178.6 2
> 0011 82.9 1206.3 1919
> 0012 5.9 16874.8 1919
> 0013 4.2 23889.2 92000
> {code}
>
> The regression comes from the "updateWatermarkHold()" function recently added
> in Flink DoFnOperator in
> [PR#10534|h[https://github.com/apache/beam/pull/10534]]
> [https://github.com/apache/beam/blob/bdd1726fd6b1103791f597f5e746ea2d205cf648/runners/flink/src/main/java/org/apache/beam/runners/flink/translation/wrappers/streaming/DoFnOperator.java#L1140]
> It's to allow FinkRunner to set watermark holds. However, the implementation
> was not performance efficient:
> # "pendingTimersById" is an interface of the RocksDB key/value map state.
> Iterate all values via "pendingTimersById.values()" is a big cost. According
> to the bellow CPU cycles profiling result of Query 4 by
> [async-profiler|[https://github.com/jvm-profiling-tools/async-profiler]], we
> also can see that most of the CPU time was spent on "RocksIterator.next()"
> brought by "pendingTimersById.values()".
> # Another overhead is that this function will be called multiple times in
> each setTimer and deleteTimer;
>
> CPU time profiling result (FlameGraph) of Query 4 in Nexmark:
> [https://drive.google.com/open?id=1muVQipv-JidxVceQkOze5PZozPgPB_bh]
>
>
>
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