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https://issues.apache.org/jira/browse/FLINK-9506?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16509818#comment-16509818
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Sihua Zhou edited comment on FLINK-9506 at 6/12/18 4:26 PM:
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Hi [~yow] What do you means by the empty ProcessAggregation? Did you use any
state in the empty ProcessAggregation? Or could you somehow provide some code
of the empty ProcessAggregation?
I think the picture related to he keyNoHash vs KeyHash is what I expected. With
hash() the key's length is only 4 bytes and the distribution is uniform,
without hash your key's length is 50 and also the distribution maybe not
uniform. But with the hash() approach you could only get a approximate result,
if that is enough for you then I think it's good to go now, is it not enough
for you?
was (Author: sihuazhou):
Hi [~yow] What do you means by the empty ProcessAggregation? Did you use any
state in the empty ProcessAggregation? Or could you somehow provide some code
of the empty ProcessAggregation?
I think the picture related to he keyNoHash vs KeyHash is what I expected.
Without hash() the key's length is only 4 bytes and the distribution is
uniform, without hash your key's length is 50 and also the distribution maybe
not uniform. But with the hash() approach you could only get a approximate
result, if that is enough for you then I think it's good to go now, is it not
enough for 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, 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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