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https://issues.apache.org/jira/browse/FLINK-9506?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16510746#comment-16510746
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swy commented on FLINK-9506:
----------------------------

Hi [~sihuazhou] it surprise me as well. Please advice if something wrong in the 
code especially to rocksdb settings. Also if you don't mind you can run the 
test in your lab and share the performance. To run the application just use the 
following sample parameters,
aggrinterval=600000 loop=5000000 auditinterval=30000 statsd=1 
URL=do36.mycompany.com:8127
thank you!

> 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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