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https://issues.apache.org/jira/browse/HADOOP-657?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12614266#action_12614266
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Vinod Kumar Vavilapalli commented on HADOOP-657:
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HADOOP-3581 tries to manage memory used by tasks. I am trying to follow the
approach of this JIRA, and have a couple of comments.
- I see that you are having free-space computation inside the task. Instead,
why can't we do it in the tasktracker itself? In this JIRA, we are caring only
about mapOutputFiles and for watching them, we just need the JOB ID and TIP ID.
Memory tracking HAS to be done in TT and not task, to shield the tracking
business itself from any rogue tasks. I think it would be good if we can manage
both these resources in TT itself, ultimately moving all of these into a single
resource management class in TT. Unless I am missing something else here.
Thoughts?
- I also see in this patch that availableSpace is sent to JT via
TaskTrackerStatus. What happened to Doug's idea of "using a general mechanism
to route metrics to the jobtracker through heartbeats, rather than hack things
in one-by-one". A general mechanism like the one Arun proposed (MetricsContext)
would also help HADOOP-3759(which intends to use freeMemory information for
scheduling decisions).
> Free temporary space should be modelled better
> ----------------------------------------------
>
> Key: HADOOP-657
> URL: https://issues.apache.org/jira/browse/HADOOP-657
> Project: Hadoop Core
> Issue Type: Improvement
> Components: mapred
> Affects Versions: 0.17.0
> Reporter: Owen O'Malley
> Assignee: Ari Rabkin
> Fix For: 0.19.0
>
> Attachments: clean_spaceest.patch, diskspaceest.patch,
> diskspaceest_v2.patch, diskspaceest_v3.patch, diskspaceest_v4.patch
>
>
> Currently, there is a configurable size that must be free for a task tracker
> to accept a new task. However, that isn't a very good model of what the task
> is likely to take. I'd like to propose:
> Map tasks: totalInputSize * conf.getFloat("map.output.growth.factor", 1.0) /
> numMaps
> Reduce tasks: totalInputSize * 2 * conf.getFloat("map.output.growth.factor",
> 1.0) / numReduces
> where totalInputSize is the size of all the maps inputs for the given job.
> To start a new task,
> newTaskAllocation + (sum over running tasks of (1.0 - done) * allocation)
> >=
> free disk * conf.getFloat("mapred.max.scratch.allocation", 0.90);
> So in English, we will model the expected sizes of tasks and only task tasks
> that should leave us a 10% margin. With:
> map.output.growth.factor -- the relative size of the transient data relative
> to the map inputs
> mapred.max.scratch.allocation -- the maximum amount of our disk we want to
> allocate to tasks.
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