Hi James,

There are over windows in Flink Table API:
https://ci.apache.org/projects/flink/flink-docs-release-1.5/dev/table/tableApi.html#over-windows
 
<https://ci.apache.org/projects/flink/flink-docs-release-1.5/dev/table/tableApi.html#over-windows>
It should be possible to implement this behaviour using them.

Cheers,
Andrey

> On 17 Jul 2018, at 18:27, Porritt, James <james.porr...@uk.mlp.com> wrote:
> 
> In Spark if I want to be able to get a set of unique rows by id, using the 
> criteria of keeping the row with the latest timestamp, I would do the 
> following:
>  
>                         .withColumn("rn",
>                             F.row_number().over(
>                                 Window.partitionBy(‘id’) \
>                                     .orderBy(F.col('timestamp').desc())
>                             )
>                         ) \
>                         .where(F.col("rn") == 1)
>  
> I see Flink has windowing functionality, but I don’t see it has row 
> enumeration? How best in that case would I achieve the above?
>  
> Thanks,
> James.
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