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