[jira] [Commented] (MAPREDUCE-4256) Improve resource scheduling

["Radim Kolar (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/MAPREDUCE-4256?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13280049#comment-13280049 ] 

Radim Kolar commented on MAPREDUCE-4256:
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Two kind of resources:

 1. cluster shared resources - every node in cluster can use them. For example WAN bandwidth.

 2. node local resources - for example GPU card.

these resources will be configured using standard hadoop configuration framework.

mapreduce.resources.cluster.available=resourcename:float,... (this option will be used by resourcemanager).
mapreduce.resources.node.available=resourcename:float (for use by nodemanager). Node manager will report available resources to resourcemanager

job config:
mapreduce.resources.mapper= list of resources needed by one mapper
mapreduce.resources.reducer= list of resources needed by one reducer

if same resource is configured per node and per cluster then per node version is preferred.
                
> Improve resource scheduling
> ---------------------------
>
>                 Key: MAPREDUCE-4256
>                 URL: https://issues.apache.org/jira/browse/MAPREDUCE-4256
>             Project: Hadoop Map/Reduce
>          Issue Type: Improvement
>          Components: resourcemanager
>            Reporter: Radim Kolar
>             Fix For: 2.0.0, 3.0.0
>
>
> Currently resource manager supports only Memory resource during container allocation.
> I propose following improvements:
> 1. add support for CPU utilization. Node CPU used information can be obtained by ResourceCalculatorPlugin.
> 2. add support for custom resources. In node configuration will be something like:
> name=node.resource.GPU, value=1 (node has 1 GPU).
> If job will need to use GPU for computation, it will add "GPU=1" requirement to its job config and Resource Manager will allocate container on node with GPU available.

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