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From "Xiang Li (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (MAPREDUCE-7100) Provide options to skip adding resource request for data-local and rack-local respectively
Date Mon, 04 Jun 2018 02:55:00 GMT

    [ https://issues.apache.org/jira/browse/MAPREDUCE-7100?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16499689#comment-16499689
] 

Xiang Li commented on MAPREDUCE-7100:
-------------------------------------

The allocation of containing is more quick if I disabled adding requests for rack-local. But
the MR job summary shows:
{code}
Rack-local map tasks=xxx
{code}
which is quite questionable to me, because I did not request rack-local containers, why are
there rack-local map tasks.


> Provide options to skip adding resource request for data-local and rack-local respectively
> ------------------------------------------------------------------------------------------
>
>                 Key: MAPREDUCE-7100
>                 URL: https://issues.apache.org/jira/browse/MAPREDUCE-7100
>             Project: Hadoop Map/Reduce
>          Issue Type: Improvement
>          Components: applicationmaster
>            Reporter: Xiang Li
>            Priority: Minor
>
> We are using hadoop 2.7.3 and the computing layer is running out of the storage cluster
(that is, node managers are running on a different set of nodes from data nodes). The problem
we meet is that the container allocation is quite slow for some jobs.
> After some debugging, we found that in org.apache.hadoop.mapreduce.v2.app.rm.RMContainerRequestor#addContainerReq()
(the following code is from trunk, not 2.7.3)
> {code}
> protected void addContainerReq(ContainerRequest req) {
>     // Create resource requests
>     for (String host : req.hosts) {
>       // Data-local
>       if (!isNodeBlacklisted(host)) {
>         addResourceRequest(req.priority, host, req.capability,
>             null);
>       }
>     }
>     // Nothing Rack-local for now
>     for (String rack : req.racks) {
>       addResourceRequest(req.priority, rack, req.capability,
>           null);
>     }
>     // Off-switch
>     addResourceRequest(req.priority, ResourceRequest.ANY, req.capability,
>         req.nodeLabelExpression);
>   }
> {code}
> It seem that the request of data-local and rack-local could be skipped when computing
layer is not the same as the storage cluster.
> If I get it correctly, req.hosts and req.racks are provided by InputFormat. If the mapper
is to read HDFS, req.hosts is the corresponding data node and req.racks is its rack. The debug
log of AM is like:
> {code}
> org.apache.hadoop.mapreduce.v2.app.rm.RMContainerRequestor: addResourceRequest: applicationId=1
priority=20 resourceName=<data-node> numContainers=1 #asks=1
> org.apache.hadoop.mapreduce.v2.app.rm.RMContainerRequestor: addResourceRequest: applicationId=1
priority=20 resourceName=<its rack> numContainers=1 #asks=2
> org.apache.hadoop.mapreduce.v2.app.rm.RMContainerRequestor: addResourceRequest: applicationId=1
priority=20 resourceName=* numContainers=1 #asks=3
> {code}
> Although eventually, the resource request with resourceName=<data-node> will not
be satisfied (because the data node is not node manager) in RM, it could be better if AM does
not request data-local or rack-local at the very beginning, when we already know that computer
layer runs out of the storage cluster.



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