Hi,

It would not be feasible actually to use kafka queues or the DFS. Could you 
point me at which level of API I could access the CoLocationConstraint? Is it 
accessible from the  DataSourceStream or from the operator directly?

I have also dig  through the documentation and API and I was curious to 
understand a bit what can the “slotSharingGroup” and “startNewResouceGroup()” 
can do.

I did not find though a good example..only this link 
https://issues.apache.org/jira/browse/FLINK-3315

Also, for the “slotSharingGroup” it doesn’t seem to be available (I am 
currently using flink 0.10) – so if it is something that came newer than I 
guess this is the explanation why I cannot find it in any of datastream api or 
source function

Thanks for the info.


From: ewenstep...@gmail.com [mailto:ewenstep...@gmail.com] On Behalf Of Stephan 
Ewen
Sent: Wednesday, March 09, 2016 6:30 PM
To: user@flink.apache.org
Subject: Re: operators

Hi!

You cannot specify that on the higher API levels. The lower API levels have 
something called "CoLocationConstraint". At this point it is not exposed, 
because we thought that would lead to not very scalable and robust designs in 
many cases
.
The best thing usually is location transparency and local affinity (as a 
performance optimization).
Is the file large, i.e., would it hurt to do it on a DFS? Or actually use a 
Kafka Queue between the operators?

Stephan


On Wed, Mar 9, 2016 at 5:38 PM, Radu Tudoran 
<radu.tudo...@huawei.com<mailto:radu.tudo...@huawei.com>> wrote:
Hi,

Is there any way in which you can ensure that 2 distinct operators will be 
executed on the same machine?
More precisely what I am trying to do is to have a window that computes some 
metrics and will dump this locally (from the operator not from an output sink) 
and I would like to create independent of this (or event within the operator) a 
stream source to emit this data. I cannot

The schema would be something as below:

Stream ->  operator   -> output
                    |
                  Local file
                      |
                    Stream source -> new stream

.=> the red items should go on the same machine

Dr. Radu Tudoran
Research Engineer - Big Data Expert
IT R&D Division

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