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https://issues.apache.org/jira/browse/YARN-624?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13659091#comment-13659091
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Carlo Curino commented on YARN-624:
-----------------------------------
Alejandro, I completely agree gang scheduling is an important and missing use
case. As I told you in person, I spoke with various machine-learning guys and
they are very interested in gang scheduling (they are working on their own AM
for ML computations). From the conversation I am convinced their asks represent
a rather common requirement for much of ML-type applications. In particular,
they were interested in the "or" use-case you mentioned.
Specifically they want to be able to express this:
1) 1 container with 128GB of RAM and 16cores OR
2) 10 containers with 16GB of RAM and 2 cores OR
3) 100 containers with 2GB of RAM and 1 core
In term of locality I can see three main scenarios:
1) absolute locality, i.e., I need a gang of N containers on this rack, or on
these set of nodes,
2) relative locality, i.e., I need a gang of N containers "close to each other"
(this really captures more of a network property than anything else)
3) (no locality), i.e., I need a gang of N containers anywhere in the cluster
> Support gang scheduling in the AM RM protocol
> ---------------------------------------------
>
> Key: YARN-624
> URL: https://issues.apache.org/jira/browse/YARN-624
> Project: Hadoop YARN
> Issue Type: Sub-task
> Components: api, scheduler
> Affects Versions: 2.0.4-alpha
> Reporter: Sandy Ryza
> Assignee: Sandy Ryza
>
> Per discussion on YARN-392 and elsewhere, gang scheduling, in which a
> scheduler runs a set of tasks when they can all be run at the same time,
> would be a useful feature for YARN schedulers to support.
> Currently, AMs can approximate this by holding on to containers until they
> get all the ones they need. However, this lends itself to deadlocks when
> different AMs are waiting on the same containers.
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