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https://issues.apache.org/jira/browse/HADOOP-1900?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel#action_12542122
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Amareshwari Sri Ramadasu commented on HADOOP-1900:
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With the patch attached, I ran sort benchmarks on 390 node cluster and 120 node 
cluster. The performance is almost the same as with the trunk.

To simulate busyness at the job tracker, I ran the sort benchmarks on 120 node 
cluster with number of handlers=4 and with max queue size per handler =10, but 
there are drops and lost task trackers with the patch and wothout. 

Thus Cluster size factor as (clusterSize/50+1) is fine. but the busy factor has 
to be tuned more.

I propose the following to tune busy factor:

threshouldDropCount = clusterSize/10;
if(dropCount > threshouldDropCount) {
  busyFactor += (dropCount/threshouldDropCount)*HEARTBEAT_BUSY_FACTOR;
}

if job tracker is not busy for '_notBusyPeriod_' , then we will decrement 
busyFactor by HEARTBEAT_BUSY_FACTOR;
We have,  2 rpcs to be processed as at the jobtracker i.e. heartbeat and task 
completion events. let processing time for rpc be 2 seconds. 
Here, notBusyPeriod is calculated as:
notBusyPeriod = (clusterSize/#handlers)*processingTime*2;

To stabilize, 
consider we have drops at t, and we increment heartbeat interval by 
busyfactor,_b_. And we notice that _b_ is small enough  and we dont see drops 
at the new interval, then we stabilize.

Thoughts?

> the heartbeat and task event queries interval should be set dynamically by 
> the JobTracker
> -----------------------------------------------------------------------------------------
>
>                 Key: HADOOP-1900
>                 URL: https://issues.apache.org/jira/browse/HADOOP-1900
>             Project: Hadoop
>          Issue Type: Improvement
>          Components: mapred
>            Reporter: Owen O'Malley
>            Assignee: Amareshwari Sri Ramadasu
>         Attachments: patch-1900.txt, patch-1900.txt
>
>
> The JobTracker should scale the intervals that the TaskTrackers use to 
> contact it dynamically, based on how the busy it is and the size of the 
> cluster.

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