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From "Jian He (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (YARN-1593) support out-of-proc AuxiliaryServices
Date Fri, 01 May 2015 20:47:07 GMT

     [ https://issues.apache.org/jira/browse/YARN-1593?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel

Jian He updated YARN-1593:
    Component/s: nodemanager
                 rolling upgrade

> support out-of-proc AuxiliaryServices
> -------------------------------------
>                 Key: YARN-1593
>                 URL: https://issues.apache.org/jira/browse/YARN-1593
>             Project: Hadoop YARN
>          Issue Type: Improvement
>          Components: nodemanager, rolling upgrade
>            Reporter: Ming Ma
> AuxiliaryServices such as ShuffleHandler currently run in the same process as NM. There
are some benefits to host them in dedicated processes.
> 1. NM rolling restart. If we want to upgrade YARN , NM restart will force the ShuffleHandler
restart. If ShuffleHandler runs as a separate process, ShuffleHandler can continue to run
during NM restart. NM can reconnect the the running ShuffleHandler after restart.
> 2. Resource management. It is possible another type of AuxiliaryServices will be implemented.
AuxiliaryServices are considered YARN application specific and could consume lots of resources.
Running AuxiliaryServices in separate processes allow easier resource management. NM could
potentially stop a specific AuxiliaryServices process from running if it consumes resource
way above its allocation.
> Here are some high level ideas:
> 1. NM provides a hosting process for each AuxiliaryService. Existing AuxiliaryService
API doesn't change.
> 2. The hosting process provides RPC server for AuxiliaryService proxy object inside NM
to connect to.
> 3. When we rolling restart NM, the existing AuxiliaryService processes will continue
to run. NM could reconnect to the running AuxiliaryService processes upon restart.
> 4. Policy and resource management of AuxiliaryServices. So far we don't have immediate
need for this. AuxiliaryService could run inside a container and its resource utilization
could be taken into account by RM and RM could consider a specific type of applications overutilize
cluster resource.

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