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https://issues.apache.org/jira/browse/OOZIE-1178?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13561468#comment-13561468
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Tianyou Li commented on OOZIE-1178:
-----------------------------------
[~acmurthy]Thanks for your response. And thank you for accepting us as part of
the project, look forward to work with you and others of this. If there are
anything we can do to help you for the legwork, please let us know. We will
wait to hear from you on how and when we can collaborate on this in the
community, meanwhile we continue to build up the solution and once it ready we
are glad to share the code with the community.
> Workflow Application Master in YARN
> -----------------------------------
>
> Key: OOZIE-1178
> URL: https://issues.apache.org/jira/browse/OOZIE-1178
> Project: Oozie
> Issue Type: New Feature
> Reporter: Bo Wang
> Attachments: MAPREDUCE-4495-v1.1.patch, MAPREDUCE-4495-v1.patch,
> MapReduceWorkflowAM.pdf, yapp_proposal.txt
>
>
> It is useful to have a workflow application master, which will be capable of
> running a DAG of jobs. The workflow client submits a DAG request to the AM
> and then the AM will manage the life cycle of this application in terms of
> requesting the needed resources from the RM, and starting, monitoring and
> retrying the application's individual tasks.
> Compared to running Oozie with the current MapReduce Application Master,
> these are some of the advantages:
> - Less number of consumed resources, since only one application master will
> be spawned for the whole workflow.
> - Reuse of resources, since the same resources can be used by multiple
> consecutive jobs in the workflow (no need to request/wait for resources for
> every individual job from the central RM).
> - More optimization opportunities in terms of collective resource requests.
> - Optimization opportunities in terms of rewriting and composing jobs in the
> workflow (e.g. pushing down Mappers).
> - This Application Master can be reused/extended by higher systems like Pig
> and hive to provide an optimized way of running their workflows.
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