Hi, I will use English because we are also sending to user@ ML.
This behavior is as expected, not a bug. Benchao gave a good explanation about the reason. I will give some further explanation. In Flink SQL, we will split an update operation (such as uv from 100 -> 101) into two separate messages, one is -[key, 100], the other is +[key, 101]. Once these two messages arrive the downstream aggregation, it will also send two result messages (assuming the previous SUM(uv) is 500), one is [key, 400], the other is [key, 501]. But this problem is almost addressed since 1.9, if you enabled the mini-batch optimization [1]. Because mini-batch optimization will try best to the accumulate the separate + and - message in a single mini-batch processing. You can upgrade and have a try. Best, Jark [1]: https://ci.apache.org/projects/flink/flink-docs-release-1.10/dev/table/tuning/streaming_aggregation_optimization.html#minibatch-aggregation On Sat, 18 Apr 2020 at 12:26, Benchao Li <[email protected]> wrote: > 这个按照目前的设计，应该不能算是bug，应该是by desigh的。 > 主要问题还是因为有两层agg，第一层的agg的retract会导致第二层的agg重新计算和下发结果。 > > dixingxing85 <[email protected]>于2020年4月18日 周六上午11:38写道： > >> 多谢benchao， >> 我这个作业的结果预期结果是每天只有一个结果，这个结果应该是越来越大的，比如： >> 20200417，86 >> 20200417，90 >> 20200417，130 >> 20200417，131 >> >> 而不应该是忽大忽小的，数字由大变小，这样的结果需求方肯定不能接受的： >> 20200417，90 >> 20200417，86 >> 20200417，130 >> 20200417，86 >> 20200417，131 >> >> 我的疑问是内层的group by产生的retract流，会影响sink吗，我是在sink端打的日志。 >> 如果flink支持这种两层group by的话，那这种结果变小的情况应该算是bug吧？ >> >> Sent from my iPhone >> >> On Apr 18, 2020, at 10:08, Benchao Li <[email protected]> wrote: >> >> >> >> Hi, >> >> 这个是支持的哈。 >> 你看到的现象是因为group by会产生retract结果，也就是会先发送-[old]，再发送+[new]. >> 如果是两层的话，就成了： >> 第一层-[old], 第二层-[cur], +[old] >> 第一层+[new], 第二层[-old], +[new] >> >> [email protected] <[email protected]> 于2020年4月18日周六 上午2:11写道： >> >>> >>> Hi all: >>> >>> 我们有个streaming sql得到的结果不正确，现象是sink得到的数据一会大一会小，*我们想确认下，这是否是个bug， >>> 或者flink还不支持这种sql*。 >>> 具体场景是：先group by A, B两个维度计算UV，然后再group by A 把维度B的UV sum起来，对应的SQL如下：（A -> >>> dt, B -> pvareaid) >>> >>> SELECT dt, SUM(a.uv) AS uv >>> FROM ( >>> SELECT dt, pvareaid, COUNT(DISTINCT cuid) AS uv >>> FROM streaming_log_event >>> WHERE action IN ('action1') >>> AND pvareaid NOT IN ('pv1', 'pv2') >>> AND pvareaid IS NOT NULL >>> GROUP BY dt, pvareaid >>> ) a >>> GROUP BY dt; >>> >>> sink接收到的数据对应日志为： >>> >>> 2020-04-17 22:28:38,727 INFO groupBy xx -> to: Tuple2 -> Sink: Unnamed >>> (1/1) (GeneralRedisSinkFunction.invoke:169) - receive >>> data(false,0,86,20200417) >>> 2020-04-17 22:28:38,727 INFO groupBy xx -> to: Tuple2 -> Sink: Unnamed >>> (1/1) (GeneralRedisSinkFunction.invoke:169) - receive >>> data(true,0,130,20200417) >>> 2020-04-17 22:28:39,327 INFO groupBy xx -> to: Tuple2 -> Sink: Unnamed >>> (1/1) (GeneralRedisSinkFunction.invoke:169) - receive >>> data(false,0,130,20200417) >>> 2020-04-17 22:28:39,327 INFO groupBy xx -> to: Tuple2 -> Sink: Unnamed >>> (1/1) (GeneralRedisSinkFunction.invoke:169) - receive >>> data(true,0,86,20200417) >>> 2020-04-17 22:28:39,327 INFO groupBy xx -> to: Tuple2 -> Sink: Unnamed >>> (1/1) (GeneralRedisSinkFunction.invoke:169) - receive >>> data(false,0,86,20200417) >>> 2020-04-17 22:28:39,328 INFO groupBy xx -> to: Tuple2 -> Sink: Unnamed >>> (1/1) (GeneralRedisSinkFunction.invoke:169) - receive >>> data(true,0,131,20200417) >>> >>> >>> 我们使用的是1.7.2， 测试作业的并行度为1。 >>> 这是对应的 issue: https://issues.apache.org/jira/browse/FLINK-17228 >>> >>> >>> ------------------------------ >>> [email protected] >>> >>> >> >> -- >> >> Benchao Li >> School of Electronics Engineering and Computer Science, Peking University >> Tel:+86-15650713730 >> Email: [email protected]; [email protected] >> >> -- > > Benchao Li > School of Electronics Engineering and Computer Science, Peking University > Tel:+86-15650713730 > Email: [email protected]; [email protected] > >
