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From "Matei Zaharia (JIRA)" <j...@apache.org>
Subject [jira] Created: (HADOOP-4667) Global scheduling in the Fair Scheduler
Date Sun, 16 Nov 2008 00:10:45 GMT
Global scheduling in the Fair Scheduler

                 Key: HADOOP-4667
                 URL: https://issues.apache.org/jira/browse/HADOOP-4667
             Project: Hadoop Core
          Issue Type: New Feature
          Components: contrib/fair-share
            Reporter: Matei Zaharia

The current schedulers in Hadoop all examine a single job on every heartbeat when choosing
which tasks to assign, choosing the job based on FIFO or fair sharing. There are inherent
limitations to this approach. For example, if the job at the front of the queue is small (e.g.
10 maps, in a cluster of 100 nodes), then on average it will launch only one local map on
the first 10 heartbeats while it is at the head of the queue. This leads to very poor locality
for small jobs. Instead, we need a more "global" view of scheduling that can look at multiple
jobs. To resolve the locality problem, we will use the following algorithm:
- If the job at the head of the queue has no local task to launch, skip it and look through
other jobs.
- If a job has been skipped for at least T seconds while waiting for a local task, stop skipping
it and allow it to launch non-local tasks.
- If no job can launch a task at all, return to the head of the queue and launch a non-local
task from the first job.
This algorithm improves locality while bounding the delay that any job experiences in launching
a task.

We will actually provide two values of T - one for data-local tasks and a longer wait for
rack-local tasks. It also turns out that whether waiting is useful depends on how many tasks
are left in the job - the probability of getting a heartbeat from a node with a local task.
Thus there may be logic for removing the wait on the last few tasks in the job.

As a related issue, once we allow global scheduling, we can launch multiple tasks per heartbeat,
as in HADOOP-3136. The initial implementation of HADOOP-3136 adversely affected performance
because it only launched multiple tasks from the same job, but with the wait rule above, we
will only do this for jobs that are allowed to launch non-local tasks.

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