blink planner支持将多sink的query优化成尽量复用重复计算部分。
1.11里用StatementSet来提交job，1.11之前用sqlUpdate/insertInto + execute提交任务
kandy.wang <kandy1...@163.com> 于2020年8月4日周二 下午5:20写道：
> FLINK SQL view相关问题：
> create view order_source
>
> as
>
> select order_id, order_goods_id, user_id,...
>
> from (
>
> ...... proctime,row_number() over(partition by order_id,
> order_goods_id order by proctime desc) as rownum
>
> from hive.temp_dw.dm_trd_order_goods/*+
> OPTIONS('properties.group.id'='flink_etl_kafka_hbase',
> 'scan.startup.mode'='latest-offset') */
>
> ) where rownum = 1 and price > 0;
>
>
>
>
> insert into hive.temp_dw.day_order_index select rowkey, ROW(cast(saleN as
> BIGINT),)
>
> from
>
> (
>
> select order_date as rowkey,
>
> sum(amount) as saleN,
>
> from order_source
>
> group by order_date
>
> );
>
>
>
>
> insert into hive.temp_dw.day_order_index select rowkey, ROW(cast(saleN as
> BIGINT))
>
> from
>
> (
>
> select order_hour as rowkey, sum(amount) as saleN,
>
>
>
> from order_source
>
> group by order_hour
>
> );
> 问题：同一个view，相同的消费group,不同的sink,产生 2个job。 这样的话，相当于2个job公用一个consumer group。
> 最后生成的job是 : a. order_source -> sink 1 b. order_source -> sink
> 2
>
>
> 本意是想通过view order_source
> （view里需要对订单数据去重）复用同一份source全量数据,对应底层可以复用同一份state数据 ，如何做到 ？
>
>
