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 HUAWEI TECHNOLOGIES Duesseldorf GmbH European Research Center Riesstrasse 25, 80992 München E-mail:
[hidden email] Mobile: +49 15209084330 Telephone: +49 891588344173
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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 <[hidden email]> wrote:
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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: [hidden email] [mailto:[hidden email]]
On Behalf Of Stephan Ewen 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 <[hidden email]> 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 HUAWEI TECHNOLOGIES Duesseldorf GmbH European Research Center Riesstrasse 25, 80992 München
E-mail: [hidden email] Mobile:
<a href="tel:%2B49%2015209084330" target="_blank">+49 15209084330 Telephone:
<a href="tel:%2B49%20891588344173" target="_blank">+49 891588344173
HUAWEI TECHNOLOGIES Duesseldorf GmbH This e-mail and its attachments contain confidential information from HUAWEI, which is intended only for
the person or entity whose address is listed above. Any use of the information contained herein in any way (including, but not limited to, total or partial disclosure, reproduction, or dissemination) by persons other than the intended recipient(s) is prohibited.
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Hi Radu, the API call If your requirement is that O_i will be executed in the same slot as P_i, then you have to add the corresponding Cheers, On Thu, Mar 10, 2016 at 2:52 PM, Radu Tudoran <[hidden email]> wrote:
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