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From "Stefan Richter (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (FLINK-9506) Flink ReducingState.add causing more than 100% performance drop
Date Wed, 13 Jun 2018 09:42:00 GMT

    [ https://issues.apache.org/jira/browse/FLINK-9506?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16510870#comment-16510870
] 

Stefan Richter commented on FLINK-9506:
---------------------------------------

[~yow] I would suggest that you discuss it on the user mailing list so that (in the spirit
of open source) others can potentially benefit from it as well.

> Flink ReducingState.add causing more than 100% performance drop
> ---------------------------------------------------------------
>
>                 Key: FLINK-9506
>                 URL: https://issues.apache.org/jira/browse/FLINK-9506
>             Project: Flink
>          Issue Type: Improvement
>    Affects Versions: 1.4.2
>            Reporter: swy
>            Priority: Major
>         Attachments: KeyNoHash_VS_KeyHash.png, flink.png, input_stop_when_timer_run.png,
keyby.png
>
>
> Hi, we found out application performance drop more than 100% when ReducingState.add is
used in the source code. In the test checkpoint is disable. And filesystem(hdfs) as statebackend.
> It could be easyly reproduce with a simple app, without checkpoint, just simply keep
storing record, also with simple reduction function(in fact with empty function would see
the same result). Any idea would be appreciated. What an unbelievable obvious issue.
> Basically the app just keep storing record into the state, and we measure how many record
per second in "JsonTranslator", which is shown in the graph. The difference between is just
1 line, comment/un-comment "recStore.add(r)".
> {code}
> DataStream<String> stream = env.addSource(new GeneratorSource(loop);
> DataStream<JSONObject> convert = stream.map(new JsonTranslator())
>                                        .keyBy()
>                                        .process(new ProcessAggregation())
>                                        .map(new PassthruFunction());  
> public class ProcessAggregation extends ProcessFunction {
>     private ReducingState<Record> recStore;
>     public void processElement(Recordr, Context ctx, Collector<Record> out) {
>         recStore.add(r); //this line make the difference
> }
> {code}
> Record is POJO class contain 50 String private member.



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