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https://issues.apache.org/jira/browse/FLINK-9506?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16510575#comment-16510575
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swy commented on FLINK-9506:
----------------------------
Hi [~sihuazhou] you are right. Fluctuation only happened when "keyby" with
State. "keyby" without State is quite stable. Unfortunately hashcode() is not
good enough for us as we need to aggregate billing data, which require high
accuracy. We are now using ListState, and keyby with a 50 characters value, it
seems a reasonable use case to me. Can I consider this a limitation in Flink?
Otherwise any advice to get through? Rocksdb already in
used(PredefinedOptions.SPINNING_DISK_OPTIMIZED_HIGH_MEM) as suggested. Thank
you for your support [~sihuazhou].
> 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, 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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