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From "Robert Joseph Evans (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (YARN-371) Consolidate resource requests in AM-RM heartbeat
Date Mon, 04 Feb 2013 15:32:13 GMT

    [ https://issues.apache.org/jira/browse/YARN-371?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13570329#comment-13570329
] 

Robert Joseph Evans commented on YARN-371:
------------------------------------------

Tom just like Arun said the memory usage changes based off of the size of the cluster vs.
the size of the request.  The current approach is on the order of the size of the cluster
where as the proposed approach is on the order of the number of desired containers.  If I
have a 100 node cluster and I am requesting 100000 map tasks the size will be O(100 nodes
+ X racks + 1) possibly * 2 if reducers are included in it. What is more it is probably exactly
the same size of request for 10000 or even 1000 tasks.  Where as the proposed approach would
grow without bound as the number of tasks also increased.

However, I also agree with Sandy that the current state compression is lossy and as such restricts
what is possible in the scheduler. I would like to understand better what the size differences
would be for various requests, both in memory and also over the wire.  It seems conceivable
to me that if the size difference is not too big, especially over the wire, we could allow
the scheduler itself to decide on its in memory representation.  This would allow for the
Capacity Scheduler to keep its current layout and allow for others to experiment with more
advanced scheduling options.  Different groups could decide which scheduler best fits their
needs and workload.  If the size is significantly larger I would like to see hard numbers
about how much better/worse it makes specific use cases.

I am also very concerned about adding too much complexity to the scheduler.  We have run into
issues where the RM will get very far behind in scheduling because it is trying to do a lot
already and eventually OOM as its event queue grows too large. 

I also don't want to change the scheduler protocol too much without first understanding how
that new protocol would impact other potential scheduling features.  There are a number of
other computing patterns that could benefit from specific scheduler support.  Things like
gang scheduling where you need all of the containers at once or none of them can make any
progress, or where you want all of the containers to be physically close to one another because
they are very I/O intensive, but you don't really care where exactly they are.  Or even something
like HBase where you essentially want one process on every single node with no duplicates.
 Do the proposed changes make these uses case trivially simple, or do they require a lot of
support on the AM to implement them?

  
                
> Consolidate resource requests in AM-RM heartbeat
> ------------------------------------------------
>
>                 Key: YARN-371
>                 URL: https://issues.apache.org/jira/browse/YARN-371
>             Project: Hadoop YARN
>          Issue Type: Improvement
>          Components: api, resourcemanager, scheduler
>    Affects Versions: 2.0.2-alpha
>            Reporter: Sandy Ryza
>            Assignee: Sandy Ryza
>
> Each AMRM heartbeat consists of a list of resource requests. Currently, each resource
request consists of a container count, a resource vector, and a location, which may be a node,
a rack, or "*". When an application wishes to request a task run in multiple localtions, it
must issue a request for each location.  This means that for a node-local task, it must issue
three requests, one at the node-level, one at the rack-level, and one with * (any). These
requests are not linked with each other, so when a container is allocated for one of them,
the RM has no way of knowing which others to get rid of. When a node-local container is allocated,
this is handled by decrementing the number of requests on that node's rack and in *. But when
the scheduler allocates a task with a node-local request on its rack, the request on the node
is left there.  This can cause delay-scheduling to try to assign a container on a node that
nobody cares about anymore.
> Additionally, unless I am missing something, the current model does not allow requests
for containers only on a specific node or specific rack. While this is not a use case for
MapReduce currently, it is conceivable that it might be something useful to support in the
future, for example to schedule long-running services that persist state in a particular location,
or for applications that generally care less about latency than data-locality.
> Lastly, the ability to understand which requests are for the same task will possibly
allow future schedulers to make more intelligent scheduling decisions, as well as permit a
more exact understanding of request load.
> I would propose the tweak of allowing a single ResourceRequest to encapsulate all the
location information for a task.  So instead of just a single location, a ResourceRequest
would contain an array of locations, including nodes that it would be happy with, racks that
it would be happy with, and possibly *.  Side effects of this change would be a reduction
in the amount of data that needs to be transferred in a heartbeat, as well in as the RM's
memory footprint, becaused what used to be different requests for the same task are now able
to share some common data.
> While this change breaks compatibility, if it is going to happen, it makes sense to do
it now, before YARN becomes beta.

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