Thanks Jamie, Yes your assumption is correct.

I can use keyBy as follows:
stream.keyBy(“pojo.field1”,”pojo.field2”,…)
Would make sense that I can use sum for example, to do its job for more than 
one field:
stream.sum(“pojo.field1”,”pojo.field2”,…)

I have created this Jira issue for it, hopefully, it will get picked someday.
https://issues.apache.org/jira/browse/FLINK-4029

-Rami


On 8 Jun 2016, at 04:25, Jamie Grier 
<ja...@data-artisans.com<mailto:ja...@data-artisans.com>> wrote:

I'm assuming what you're trying to do is essentially sum over two different 
fields of your data.  I would do this with my own ReduceFunction.


stream
  .keyBy("someKey")
  .reduce(CustomReduceFunction) // sum whatever fields you want and return the 
result

I think it does make sense that Flink could provide a generic sum function that 
could sum over multiple fields, though.

-Jamie


On Tue, Jun 7, 2016 at 5:41 AM, Al-Isawi Rami 
<rami.al-is...@comptel.com<mailto:rami.al-is...@comptel.com>> wrote:
Hi,

Is there any reason why “keyBy" accepts multi-field, while for example “sum” 
does not.

-Rami
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