Re:Re: Flink SQL Count Distinct performance optimization

Posted by sunfulin on
URL: http://deprecated-apache-flink-user-mailing-list-archive.369.s1.nabble.com/Flink-SQL-Count-Distinct-performance-optimization-tp32003p32006.html

hi，godfreyhe

As far as I can see, I rewrite the running sql from one count distinct level to 2 level agg, just as the table.optimizer.distinct-agg.split.enabled param worked. Correct me if I am telling the wrong way. But the rewrite sql does not work well for the performance throughout. 

For now I am not able to use blink planner on my apps because the current prod environment has not planned or ready to up to Flink 1.9+. 

At 2020-01-08 15:52:28, "贺小令" <[hidden email]> wrote:

hi sunfulin,  

you can try with blink planner (since 1.9 +), which optimizes distinct aggregation. you can also try to enable table.optimizer.distinct-agg.split.enabled if the data is skew.

best,

godfreyhe

sunfulin <[hidden email]> 于2020年1月8日周三 下午3:39写道：

Hi, community,
I'm using Apache Flink SQL to build some of my realtime streaming apps. With one scenario I'm trying to count(distinct deviceID) over about 100GB data set in realtime, and aggregate results with sink to ElasticSearch index. I met a severe performance issue when running my flink job. Wanner get some help from community.


Flink version : 1.8.2
Running on yarn with 4 yarn slots per task manager. My flink task parallelism is set to be 10, which is equal to my kafka source partitions. After running the job, I can observe high backpressure from the flink dashboard. Any suggestions and kind of help is highly appreciated.


running sql is like the following:


INSERT INTO ES6_ZHANGLE_OUTPUT(aggId, pageId, ts, expoCnt, clkCnt)

select aggId, pageId, statkey as ts, sum(cnt) as expoCnt, count(cnt) as clkCnt  from

(

    SELECT

     aggId,

     pageId,

     statkey,

     COUNT(DISTINCT deviceId) as cnt

     FROM

     (

         SELECT

         'ZL_005' as aggId,

         'ZL_UV_PER_MINUTE' as pageId,

         deviceId,

         ts2Date(recvTime) as statkey

         from

         kafka_zl_etrack_event_stream

     )

     GROUP BY aggId, pageId, statkey, MOD(hashCode(deviceId), 1024)

) as t1

group by aggId, pageId, statkey
















Best