[
https://issues.apache.org/jira/browse/YARN-3215?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15096466#comment-15096466
]
Sunil G commented on YARN-3215:
-------------------------------
Thanks [~Naganarasimha Garla] for pushing this ticket. I had one doubt here.
{code}
+ Resource getQueueMaxResource(String nodePartition, Resource clusterResource)
{
+ return Resources.multiplyAndNormalizeDown(resourceCalculator,
+ labelManager.getResourceByLabel(nodePartition, clusterResource),
+ queueCapacities.getAbsoluteMaximumCapacity(nodePartition),
minimumAllocation);
+ }
{code}
{{getAbsoluteMaximumCapacity}} is used here. In LeafQueue#getHeadroom,
{{currentPartitionResourceLimit}} is now derived from this max capacity of a
queue (per label).
So could this be a bigger value considering same label may present in multiple
queues. Thus by projecting more headroom, is there chance that more requests
may be pushed by different applications in different queues (but same label).
Pls correct me if I am wrong.
> Respect labels in CapacityScheduler when computing headroom
> -----------------------------------------------------------
>
> Key: YARN-3215
> URL: https://issues.apache.org/jira/browse/YARN-3215
> Project: Hadoop YARN
> Issue Type: Sub-task
> Components: capacityscheduler
> Reporter: Wangda Tan
> Assignee: Naganarasimha G R
> Attachments: YARN-3215.v1.001.patch
>
>
> In existing CapacityScheduler, when computing headroom of an application, it
> will only consider "non-labeled" nodes of this application.
> But it is possible the application is asking for labeled resources, so
> headroom-by-label (like 5G resource available under node-label=red) is
> required to get better resource allocation and avoid deadlocks such as
> MAPREDUCE-5928.
> This JIRA could involve both API changes (such as adding a
> label-to-available-resource map in AllocateResponse) and also internal
> changes in CapacityScheduler.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
