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Re: Re: Flink streaming sql是否支持两层group by聚合

Posted by dixingxing85@163.com on
URL: http://deprecated-apache-flink-user-mailing-list-archive.369.s1.nabble.com/Flink-streaming-sql-group-by-tp34412p34432.html

@Benchao  @Jark  
thank you very much. We have use flink 1.9 for a while , and we will try 1.9 + minibatch. 

 
Send Time: 2020-04-18 21:38
Receiver: [hidden email]
Subject: Re: Flink streaming sql是否支持两层group by聚合
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




On Sat, 18 Apr 2020 at 12:26, Benchao Li <[hidden email]> 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 <[hidden email]>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 <[hidden email]> 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]

[hidden email] <[hidden email]> 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。




-- 
Benchao Li
School of Electronics Engineering and Computer Science, Peking University
Tel:+86-15650713730
Email: [hidden email]; [hidden email]
-- 
Benchao Li
School of Electronics Engineering and Computer Science, Peking University
Tel:+86-15650713730
Email: [hidden email]; [hidden email]
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