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Posted to yarn-issues@hadoop.apache.org by "Wangda Tan (JIRA)" <ji...@apache.org> on 2015/07/29 22:23:05 UTC

[jira] [Updated] (YARN-3983) Make CapacityScheduler to easier extend application allocation logic

     [ https://issues.apache.org/jira/browse/YARN-3983?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Wangda Tan updated YARN-3983:
-----------------------------
    Attachment: YARN-3983.1.patch

Attached initial patch for review.

> Make CapacityScheduler to easier extend application allocation logic
> --------------------------------------------------------------------
>
>                 Key: YARN-3983
>                 URL: https://issues.apache.org/jira/browse/YARN-3983
>             Project: Hadoop YARN
>          Issue Type: Bug
>            Reporter: Wangda Tan
>            Assignee: Wangda Tan
>         Attachments: YARN-3983.1.patch
>
>
> While working on YARN-1651 (resource allocation for increasing container), I found it is very hard to extend existing CapacityScheduler resource allocation logic to support different types of resource allocation.
> For example, there's a lot of differences between increasing a container and allocating a container:
> - Increasing a container doesn't need to check locality delay.
> - Increasing a container doesn't need to build/modify a resource request tree (ANY->RACK/HOST).
> - Increasing a container doesn't need to check allocation/reservation starvation (see {{shouldAllocOrReserveNewContainer}}).
> - After increasing a container is approved by scheduler, it need to update an existing container token instead of creating new container.
> And there're lots of similarities when allocating different types of resources.
> - User-limit/queue-limit will be enforced for both of them.
> - Both of them needs resource reservation logic. (Maybe continuous reservation looking is needed for both of them).
> The purpose of this JIRA is to make easier extending CapacityScheduler resource allocation logic to support different types of resource allocation, make common code reusable, and also better code organization.



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