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From Ravi Prakash <ravihad...@gmail.com>
Subject Re: Yarn 2.7.3 - capacity scheduler container allocation to nodes?
Date Thu, 10 Nov 2016 01:48:07 GMT
Hi Rafal!

Have you been able to launch the job successfully first without configuring
node-labels? Do you really need node-labels? How much total memory do you
have on the cluster? Node labels are usually for specifying special
capabilities of the nodes (e.g. some nodes could have GPUs and your
application could request to be run on only the nodes which have GPUs)


On Wed, Nov 9, 2016 at 5:37 AM, RafaƂ Radecki <radecki.rafal@gmail.com>

> Hi All.
> I have a 4 node cluster on which I run yarn. I created 2 queues "long" and
> "short", first with 70% resource allocation, the second with 30%
> allocation. Both queues are configured on all available nodes by default.
> My memory for yarn per node is ~50GB. Initially I thought that when I will
> run tasks in "short" queue yarn will allocate them on all nodes using 30%
> of the memory on every node. So for example if I run 20 tasks, 2GB each
> (40GB summary), in short queue:
> - ~7 first will be scheduled on node1 (14GB total, 30% out of 50GB
> available on this node for "short" queue -> 15GB)
> - next ~7 tasks will be scheduled on node2
> - ~6 remaining tasks will be scheduled on node3
> - yarn on node4 will not use any resources assigned to "short" queue.
> But this seems not to be the case. At the moment I see that all tasks are
> started on node1 and other nodes have no tasks started.
> I attached my yarn-site.xml and capacity-scheduler.xml.
> Is there a way to force yarn to use configured above thresholds (70% and
> 30%) per node and not per cluster as a whole? I would like to get a
> configuration in which on every node 70% is always available for "short"
> queue, 70% for "long" queue and in case any resources are free for a
> particular queue they are not used by other queues. Is it possible?
> BR,
> Rafal.
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