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 <libenc...@gmail.com> 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]
>
> dixingxin...@163.com <dixingxin...@163.com> 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
>>
>>
>> dixingxin...@163.com
>
>
> --
> Benchao Li
> School of Electronics Engineering and Computer Science, Peking University
> Tel:+86-15650713730
> Email: libenc...@gmail.com; libenc...@pku.edu.cn
