Hi admin, 不会丢弃数据哈,会重复提交Partition(所以现在partition的提交都是幂等操作)
On Thu, Nov 12, 2020 at 3:11 PM admin <17626017...@163.com> wrote: > 补充一下不用partition time trigger的原因,partition > time是基于watermark的,当数据延迟比较严重时,会丢弃数据吧,这种情况是不能接受的 > > > 2020年11月12日 下午2:15,admin <17626017...@163.com> 写道: > > > > Hi ,kandy > > 我没有基于partition time 提交分区,我是基于默认的process > time,所以是可以多次提交分区的,我知道在当前分区内的乱序数据可以提交,但是有延迟时间比较长的数据(比如上面的例子)是否还能被提交到对应分区 > > > >> 2020年11月12日 下午12:46,kandy.wang <kandy1...@163.com> 写道: > >> > >> hi: > >> 按照我的理解,partition time提交分区,是会在current watermark > partition time + > commit delay 时机触发分区提交,得看你的sink.partition-commit.delay > >> 设置的多久,如果超过之后,应当默认是会丢弃的吧。 > >> > >> > >> https://cloud.tencent.com/developer/article/1707182 > >> > >> 这个连接可以看一下 > >> > >> > >> > >> > >> > >> > >> > >> 在 2020-11-12 11:58:22,"admin" <17626017...@163.com> 写道: > >>> Hi,all > >>> Flink 1.11的filesystem connector,partition trigger[1]都是使用的默认值,所以分区可以多次提交 > >>> 现在有这样的场景: > >>> 消费kafka数据写入hdfs中,分区字段是 day + hour > ,是从事件时间截取出来的,如果数据延迟了,比如现在是19点了,来了17点的数据, > >>> 这条数据还能正确的写到17点分区里面吗?还是写到19点分区?还是会被丢弃? > >>> 有大佬知道吗,有实际验证过吗 > >>> 感谢 > >>> > >>> 附上简单sql: > >>> CREATE TABLE kafka ( > >>> a STRING, > >>> b STRING, > >>> c BIGINT, > >>> process_time BIGINT, > >>> e STRING, > >>> f STRING, > >>> g STRING, > >>> h INT, > >>> i STRING > >>> ) WITH ( > >>> 'connector' = 'kafka', > >>> 'topic' = 'topic', > >>> 'properties.bootstrap.servers' = 'x', > >>> 'properties.group.id' = 'test-1', > >>> 'scan.startup.mode' = 'latest-offset', > >>> 'format' = 'json', > >>> 'properties.flink.partition-discovery.interval-millis' = '300000' > >>> ); > >>> > >>> CREATE TABLE filesystem ( > >>> `day` STRING, > >>> `hour` STRING, > >>> a STRING, > >>> b STRING, > >>> c BIGINT, > >>> d BIGINT, > >>> e STRING, > >>> f STRING, > >>> g STRING, > >>> h INT, > >>> i STRING > >>> ) PARTITIONED BY (`day`, `hour`) WITH ( > >>> 'connector' = 'filesystem', > >>> 'format' = 'parquet', > >>> 'path' = 'hdfs://xx', > >>> 'parquet.compression'='SNAPPY', > >>> 'sink.partition-commit.policy.kind' = 'success-file' > >>> ); > >>> > >>> insert into filesystem > >>> select > >>> from_unixtime(process_time,'yyyy-MM-dd') as `day`, > >>> from_unixtime(process_time,'HH') as `hour`, > >>> a, > >>> b, > >>> c, > >>> d, > >>> e, > >>> f, > >>> g, > >>> h, > >>> i > >>> from kafka; > >>> > >>> > >>> > >>> [1] > https://ci.apache.org/projects/flink/flink-docs-release-1.11/dev/table/connectors/filesystem.html#partition-commit-trigger > > > > -- Best, Jingsong Lee