[jira] Assigned: (HADOOP-3376) [HOD] HOD should have a way to detect and deal with clusters that violate/exceed resource manager limits

["Vinod Kumar Vavilapalli (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/HADOOP-3376?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Vinod Kumar Vavilapalli reassigned HADOOP-3376:
-----------------------------------------------

    Assignee: Vinod Kumar Vavilapalli  (was: Hemanth Yamijala)

> [HOD] HOD should have a way to detect and deal with clusters that violate/exceed resource manager limits
> --------------------------------------------------------------------------------------------------------
>
>                 Key: HADOOP-3376
>                 URL: https://issues.apache.org/jira/browse/HADOOP-3376
>             Project: Hadoop Core
>          Issue Type: Bug
>          Components: contrib/hod
>            Reporter: Vinod Kumar Vavilapalli
>            Assignee: Vinod Kumar Vavilapalli
>
> Currently If we set up resource manager/scheduler limits on the jobs submitted, any HOD cluster that exceeds/violates these limits may 1) get blocked/queued indefinitely or 2) blocked till resources occupied by old clusters get freed. HOD should detect these scenarios and deal intelligently, instead of just waiting for a long time/ for ever. This means more and proper information to the submitter.
> (Internal) Use Case:
>      If there are no resource limits, users can flood the resource manager queue preventing other users from using the queue. To avoid this, we could have various types of limits setup in either resource manager or a scheduler - max node limit in torque(per job limit), maxproc limit in maui (per user/class), maxjob limit in maui(per user/class) etc. But there is one problem with the current setup - for e.g if we set up maxproc limit in maui to limit the aggregate number of nodes by any user over all jobs, 1) jobs get queued indefinitely if jobs exceed max limit and 2) blocked if it asks for nodes < max limit, but some of the resources are already used by jobs from the same user. This issue addresses how to deal with scenarios like these.

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