Re: Streaming : a way to "key by partition id" without redispatching data

[Derek VerLee]

I was about to ask this question myself.  I find myself re-keying by the same keys repeatedly.  I think in principle you could always just roll more work into one window operation with a more complex series of maps/folds/windowfunctions or processfunction.  However this doesn't always feel the most clean or convenient, or composible.  It would be great if there was a way to just express that you want to keep the same partitions as the last window, or that the new key is 1-to-1 with the previous one.  Even more generally, if the new key is "based" off the old key in a way that is one to one or one to many, in either case it may not be necessary to send data over the wire, although in the later case, there is a risk of hot-spotting , I suppose. On 11/10/17 12:01 PM, Gwenhael Pasquiers wrote: I think I finally found a way to “simulate” a Timer thanks to the the processWatermark function of the AbstractStreamOperator.   Sorry for the monologue.   From: Gwenhael Pasquiers [mailto:gwenhael.pasqui...@ericsson.com] Sent: vendredi 10 novembre 2017 16:02 To: 'user@flink.apache.org' <user@flink.apache.org> Subject: RE: Streaming : a way to "key by partition id" without redispatching data   Hello,   Finally, even after creating my operator, I still get the error : “Timers can only be used on keyed operators”.   Isn’t there any way around this ? A way to “key” my stream without shuffling the data ?   From: Gwenhael Pasquiers Sent: vendredi 10 novembre 2017 11:42 To: Gwenhael Pasquiers <gwenhael.pasqui...@ericsson.com>; 'user@flink.apache.org' <user@flink.apache.org> Subject: RE: Streaming : a way to "key by partition id" without redispatching data   Maybe you don’t need to bother with that question.   I’m currently discovering AbstractStreamOperator, OneInputStreamOperator and Triggerable.   That should do it :-)   From: Gwenhael Pasquiers [mailto:gwenhael.pasqui...@ericsson.com] Sent: jeudi 9 novembre 2017 18:00 To: 'user@flink.apache.org' <user@flink.apache.org> Subject: Streaming : a way to "key by partition id" without redispatching data   Hello,   (Flink 1.2.1)   For performances reasons I’m trying to reduce the volume of data of my stream as soon as possible by windowing/folding it for 15 minutes before continuing to the rest of the chain that contains keyBys and windows that will transfer data everywhere.   Because of the huge volume of data, I want to avoid “moving” the data between partitions as much as possible (not like a naïve KeyBy does). I wanted to create a custom ProcessFunction (using timer and state to fold data for X minutes) in order to fold my data over itself before keying the stream but even ProcessFunction needs a keyed stream…   Is there a specific “key” value that would ensure me that my data won’t be moved to another taskmanager (that it’s hashcode will match the partition it is already in) ? I thought about the subtask id but I doubt I’d be that lucky :-)   Suggestions ·         Wouldn’t it be useful to be able to do a “partitionnedKeyBy” that would not move data between nodes, for windowing operations that can be parallelized. o   Something like kafka => partitionnedKeyBy(0) => first folding => keyBy(0) => second folding => …. ·         Finally, aren’t all streams keyed ? Even if they’re keyed by a totally arbitrary partition id until the user chooses its own key, shouldn’t we be able to do a window (not windowAll) or process over any normal Stream’s partition ?   B.R.   Gwenhaël PASQUIERS