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Date: Mon, 5 Jan 2015 22:58:35 +0000 (UTC)
From: "Vijay Bhat (JIRA)" <jira@apache.org>
To: yarn-issues@hadoop.apache.org
Message-ID: <JIRA.12724311.1403996506000.14370.1420498715328@Atlassian.JIRA>
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 <JIRA.12724311.1403996506821@arcas>
Subject: [jira] [Commented] (YARN-2230) Fix description of
 yarn.scheduler.maximum-allocation-vcores in yarn-default.xml (or code)
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    [ https://issues.apache.org/jira/browse/YARN-2230?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14265276#comment-14265276 ] 

Vijay Bhat commented on YARN-2230:
----------------------------------

Jian,

I (Vijay Bhat) can definitely take care of that. Also, since this is my first submission, I wanted to clarify - is the protocol that I assign the JIRA to myself once I submit the patch? Apologies for any confusion. Thanks!


> Fix description of yarn.scheduler.maximum-allocation-vcores in yarn-default.xml (or code)
> -----------------------------------------------------------------------------------------
>
>                 Key: YARN-2230
>                 URL: https://issues.apache.org/jira/browse/YARN-2230
>             Project: Hadoop YARN
>          Issue Type: Bug
>          Components: client, documentation, scheduler
>    Affects Versions: 2.4.0
>            Reporter: Adam Kawa
>            Priority: Minor
>         Attachments: YARN-2230.001.patch
>
>
> When a user requests more vcores than the allocation limit (e.g. mapreduce.map.cpu.vcores  is larger than yarn.scheduler.maximum-allocation-vcores), then InvalidResourceRequestException is thrown - https://svn.apache.org/repos/asf/hadoop/common/trunk/hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-resourcemanager/src/main/java/org/apache/hadoop/yarn/server/resourcemanager/scheduler/SchedulerUtils.java
> {code}
>     if (resReq.getCapability().getVirtualCores() < 0 ||
>         resReq.getCapability().getVirtualCores() >
>         maximumResource.getVirtualCores()) {
>       throw new InvalidResourceRequestException("Invalid resource request"
>           + ", requested virtual cores < 0"
>           + ", or requested virtual cores > max configured"
>           + ", requestedVirtualCores="
>           + resReq.getCapability().getVirtualCores()
>           + ", maxVirtualCores=" + maximumResource.getVirtualCores());
>     }
> {code}
> According to documentation - yarn-default.xml http://hadoop.apache.org/docs/current/hadoop-yarn/hadoop-yarn-common/yarn-default.xml, the request should be capped to the allocation limit.
> {code}
>   <property>
>     <description>The maximum allocation for every container request at the RM,
>     in terms of virtual CPU cores. Requests higher than this won't take effect,
>     and will get capped to this value.</description>
>     <name>yarn.scheduler.maximum-allocation-vcores</name>
>     <value>32</value>
>   </property>
> {code}
> This means that:
> * Either documentation or code should be corrected (unless this exception is handled elsewhere accordingly, but it looks that it is not).
> This behavior is confusing, because when such a job (with mapreduce.map.cpu.vcores is larger than yarn.scheduler.maximum-allocation-vcores) is submitted, it does not make any progress. The warnings/exceptions are thrown at the scheduler (RM) side e.g.
> {code}
> 2014-06-29 00:34:51,469 WARN org.apache.hadoop.yarn.server.resourcemanager.ApplicationMasterService: Invalid resource ask by application appattempt_1403993411503_0002_000001
> org.apache.hadoop.yarn.exceptions.InvalidResourceRequestException: Invalid resource request, requested virtual cores < 0, or requested virtual cores > max configured, requestedVirtualCores=32, maxVirtualCores=3
> 	at org.apache.hadoop.yarn.server.resourcemanager.scheduler.SchedulerUtils.validateResourceRequest(SchedulerUtils.java:237)
> 	at org.apache.hadoop.yarn.server.resourcemanager.RMServerUtils.validateResourceRequests(RMServerUtils.java:80)
> 	at org.apache.hadoop.yarn.server.resourcemanager.ApplicationMasterService.allocate(ApplicationMasterService.java:420)
>         .....
> 	at org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:585)
> 	at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:1026)
> 	at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:1986)
> 	at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:1982)
> 	at java.security.AccessController.doPrivileged(Native Method)
> 	at javax.security.auth.Subject.doAs(Subject.java:416)
> 	at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1548)
> 	at org.apache.hadoop.ipc.Server$Handler.run(Server.java:1980)
> {code}
> * IMHO, such an exception should be forwarded to client. Otherwise, it is non obvious to discover why a job does not make any progress.
> The same looks to be related to memory.


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