Thank you Aljoscha,
I guessed that I should use the reduce method. However, I do not look
for window aggregations. I want to do this on a grouped stream.
The problem is we work with Lists instead of tuples and thus we can not
use the pre-implemented aggregates.
So the idea is to call it like that:
val aggr = source.groupBy(_(0)).reduce(new customReducer(1))
And this is the signature of the class:
class customReducer(field: Int) extends RichReduceFunction[List[Any]]
How do I have to implement this class now, so that it is working
correctly even with parallelism > 1?
I hope you understand what I try to do. =)
Kind Regards,
Philipp
On 21.08.2015 15:28, Aljoscha Krettek wrote:
Hi,
with the current API this should do what you are after:
val input = ...
val result = input
.window(...)
.groupBy(...)
.reduceWindow( /* your reduce function */ )
With the reduce function you should be able to implement any custom
aggregations. You can also use foldWindow() if you want to do a
functional fold over the window.
I hope this helps.
Cheers,
Aljoscha
On Fri, 21 Aug 2015 at 14:51 Philipp Goetze
<philipp.goe...@tu-ilmenau.de <mailto:philipp.goe...@tu-ilmenau.de>>
wrote:
Hello community,
how do I define a custom aggregate function in Flink Streaming
(Scala)?
Could you please provide an example on how to do that?
Thank you and best regards,
Philipp
