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https://issues.apache.org/jira/browse/HADOOP-3876?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12655487#action_12655487
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Hemanth Yamijala commented on HADOOP-3876:
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David,
Some clarifications:
- We do not support Condor in HOD, only Torque
- HOD serves its purpose well as a good provisioning system for Hadoop, and is
likely to live on to assist test environments where a large cluster can be
shared by multiple developers / testers each having their own version of Hadoop
to deploy and test.
- I think it it unlikely for HOD to exist as a scheduling solution for Hadoop,
built on top of the resource managers you've mentioned in your comment. That
functionality is added by scheduling solutions being built into Hadoop itself -
for e.g. the Capacity Scheduler (HADOOP-3445) and the Fair Scheduler
(HADOOP-3746).
- We did consider adding support for other resource managers in HOD, precisely
for reasons you state - it will have an easier entry into places which are
using other open source resource manager / scheduling solutions. However, given
the shift in direction from HOD, this consideration did not proceed further.
- The API in HOD did plan for accomodating other schedulers - you could look at
src/contrib/hod/hodlib/Hod/nodePool.py. It is likely that the abstraction may
not be fully suitable, but still this would be the place to start if we want to
plugin support for other schedulers.
Hope that answers some of your questions.
> Hadoop Core should support source filesfor multiple schedulers
> --------------------------------------------------------------
>
> Key: HADOOP-3876
> URL: https://issues.apache.org/jira/browse/HADOOP-3876
> Project: Hadoop Core
> Issue Type: New Feature
> Reporter: Vivek Ratan
>
> Besides the default JT scheduling algorithm, there is work going on with at
> least two more schedulers (HADOOP-3445, HADOOP-3746). HADOOP-3412 makes it
> easier to plug in new schedulers into the JT. Where do we place the source
> files for various schedulers so that it's easy for users to choose their
> scheduler of choice during deployment, and easy for developers to add in more
> schedulers into the framework (without inundating it).
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