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From "Arun C Murthy (JIRA)" <j...@apache.org>
Subject [jira] [Comment Edited] (YARN-371) Consolidate resource requests in AM-RM heartbeat
Date Fri, 01 Feb 2013 23:58:12 GMT

    [ https://issues.apache.org/jira/browse/YARN-371?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13569277#comment-13569277
] 

Arun C Murthy edited comment on YARN-371 at 2/1/13 11:56 PM:
-------------------------------------------------------------

{quote}
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.
{quote}

-1

The main advantage of the existing model is that it is extremely compact in terms of the amount
of state necessary, per application, on the ResourceManager for scheduling and the amount
of information passed around between the ApplicationMaster & ResourceManager. This is
crucial for scaling the ResourceManager. The amount of information, per application, in this
model is always O(cluster size), whereas in the current Hadoop Map-Reduce JobTracker it is
O(number of tasks) which could run into hundreds of thousands of tasks. For large jobs it
is sufficient to ask for containers only on racks and not specific hosts since the ApplicationMaster
can use them appropriately since each rack has many appropriate resources (i.e. input splits
for MapReduce applications).

To be clear, we should avoid *task* specific view and stay 'resource-specific' view.
                
      was (Author: acmurthy):
    {quote}
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.
{quote}

-1

The main advantage of the proposed model is that it is extremely compact in terms of the amount
of state necessary, per application, on the ResourceManager for scheduling and the amount
of information passed around between the ApplicationMaster & ResourceManager. This is
crucial for scaling the ResourceManager. The amount of information, per application, in this
model is always O(cluster size), whereas in the current Hadoop Map-Reduce JobTracker it is
O(number of tasks) which could run into hundreds of thousands of tasks. For large jobs it
is sufficient to ask for containers only on racks and not specific hosts since the ApplicationMaster
can use them appropriately since each rack has many appropriate resources (i.e. input splits
for MapReduce applications).

To be clear, we should avoid *task* specific view and stay 'resource-specific' view.
                  
> 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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