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https://issues.apache.org/jira/browse/HADOOP-3136?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12631662#action_12631662
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Arun C Murthy commented on HADOOP-3136:
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Ok, we really need to get better scheduling to go along with assigning multiple
tasks -- blindly assigning multiple tasks, per the current patch, has a very
negative effect on locality of tasks as TaskTrackers 'steal'
data-local/rack-local tasks from each other and consequently adversely affects
jobs. This patch slowed GridMix down by around 30%.
Here are some hallway ideas we threw around today for _better_ scheduling which
is imperative for assigning multiple tasks:
1. Oversubscribe Slots
In this approach we need to assign more than one task per slot and queue them
up at the TaskTracker. This approach allows for much larger heartbeat intervals
(the TaskTracker has queued-up work to finish) and helps with scaling out
clusters.
2. Pre-allocation of tasks to TaskTrackers via Global Scheduling
Here we build up queues for _each_ TaskTracker (and each Rack) at the
JobTracker based on locality. Each task might be on multiple queues depending
on which DataNode/TaskTracker it's data is present. When a TaskTracker
advertises empty slots we just pick off it's list and assign it. Basically this
implies that we consider the 'global' picture during scheduling and ensures
that TaskTrackers do not 'steal' data-local tasks from each other.
Of course to ensure that the highest-priority job doesn't get _starved_ we
need to assign atleast one of it's tasks on each TaskTracker's heartbeat, even
if it means we schedule an off-rack task. Similarly, to avoid spreading
task-allocation too thin i.e. across too many jobs, we need to ensure that that
the TaskTrackers' lists only contain tasks from a reasonably small set of the
highest-priority jobs.
3. HADOOP-2014: Scheduling off-rack tasks
----
Thoughts?
> Assign multiple tasks per TaskTracker heartbeat
> -----------------------------------------------
>
> Key: HADOOP-3136
> URL: https://issues.apache.org/jira/browse/HADOOP-3136
> Project: Hadoop Core
> Issue Type: Improvement
> Components: mapred
> Reporter: Devaraj Das
> Assignee: Arun C Murthy
> Fix For: 0.19.0
>
> Attachments: HADOOP-3136_0_20080805.patch,
> HADOOP-3136_1_20080809.patch, HADOOP-3136_2_20080911.patch
>
>
> In today's logic of finding a new task, we assign only one task per heartbeat.
> We probably could give the tasktracker multiple tasks subject to the max
> number of free slots it has - for maps we could assign it data local tasks.
> We could probably run some logic to decide what to give it if we run out of
> data local tasks (e.g., tasks from overloaded racks, tasks that have least
> locality, etc.). In addition to maps, if it has reduce slots free, we could
> give it reduce task(s) as well. Again for reduces we could probably run some
> logic to give more tasks to nodes that are closer to nodes running most maps
> (assuming data generated is proportional to the number of maps). For e.g., if
> rack1 has 70% of the input splits, and we know that most maps are data/rack
> local, we try to schedule ~70% of the reducers there.
> Thoughts?
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