Re: 关于row number over的用法

[Jark Wu]

Hi

你的 query 并不是 topn 语法。 可以先看这篇文档了解 topn 语法： 
http://blink.flink-china.org/dev/table/sql.html#topn 



Best,
Jark


> 在 2019年8月26日，19:02，ddwcg <3149768...@qq.com> 写道：
> 
> 
> 文档上还没有更新topN怎么使用，我尝试用row_number() over() 跑了一下，但是报错，请问topN可以是RetractStream吗？
> 
> 
> 
> 
> val monthstats = bsTableEnv.sqlQuery(
>  """
>|select
>|id,province,amount,
>|row_number() over(partition by id,province order by amount ) as rn
>|from mytable where type=1
>|group by
>|id,province,amount
>  """.stripMargin
> )
> monthstats.toRetractStream[Row].print()
> Exception in thread "main" org.apache.flink.table.api.TableException: 
> Retraction on Over window aggregation is not supported yet. Note: Over window 
> aggregation should not follow a non-windowed GroupBy aggregation.
>   at 
> org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecOverAggregate.translateToPlanInternal(StreamExecOverAggregate.scala:178)
>   at 
> org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecOverAggregate.translateToPlanInternal(StreamExecOverAggregate.scala:56)
>   at 
> org.apache.flink.table.planner.plan.nodes.exec.ExecNode$class.translateToPlan(ExecNode.scala:54)
>   at 
> org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecOverAggregate.translateToPlan(StreamExecOverAggregate.scala:56)
>   at 
> org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecSink.translateToTransformation(StreamExecSink.scala:185)
>   at 
> org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecSink.translateToPlanInternal(StreamExecSink.scala:154)
>   at 
> org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecSink.translateToPlanInternal(StreamExecSink.scala:50)
>   at 
> org.apache.flink.table.planner.plan.nodes.exec.ExecNode$class.translateToPlan(ExecNode.scala:54)
>   at 
> org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecSink.translateToPlan(StreamExecSink.scala:50)
>   at 
> org.apache.flink.table.planner.delegation.StreamPlanner$$anonfun$translateToPlan$1.apply(StreamPlanner.scala:61)
>   at 
> org.apache.flink.table.planner.delegation.StreamPlanner$$anonfun$translateToPlan$1.apply(StreamPlanner.scala:60)

关于row number over的用法

[ddwcg]

文档上还没有更新topN怎么使用，我尝试用row_number() over() 跑了一下，但是报错，请问topN可以是RetractStream吗？




val monthstats = bsTableEnv.sqlQuery(
  """
|select
|id,province,amount,
|row_number() over(partition by id,province order by amount ) as rn
|from mytable where type=1
|group by
|id,province,amount
  """.stripMargin
)
monthstats.toRetractStream[Row].print()
Exception in thread "main" org.apache.flink.table.api.TableException: 
Retraction on Over window aggregation is not supported yet. Note: Over window 
aggregation should not follow a non-windowed GroupBy aggregation.
at 
org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecOverAggregate.translateToPlanInternal(StreamExecOverAggregate.scala:178)
at 
org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecOverAggregate.translateToPlanInternal(StreamExecOverAggregate.scala:56)
at 
org.apache.flink.table.planner.plan.nodes.exec.ExecNode$class.translateToPlan(ExecNode.scala:54)
at 
org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecOverAggregate.translateToPlan(StreamExecOverAggregate.scala:56)
at 
org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecSink.translateToTransformation(StreamExecSink.scala:185)
at 
org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecSink.translateToPlanInternal(StreamExecSink.scala:154)
at 
org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecSink.translateToPlanInternal(StreamExecSink.scala:50)
at 
org.apache.flink.table.planner.plan.nodes.exec.ExecNode$class.translateToPlan(ExecNode.scala:54)
at 
org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecSink.translateToPlan(StreamExecSink.scala:50)
at 
org.apache.flink.table.planner.delegation.StreamPlanner$$anonfun$translateToPlan$1.apply(StreamPlanner.scala:61)
at 
org.apache.flink.table.planner.delegation.StreamPlanner$$anonfun$translateToPlan$1.apply(StreamPlanner.scala:60)