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From "Mayank Bansal (JIRA)" <j...@apache.org>
Subject [jira] [Created] (YARN-2670) Adding feedback capability to capacity scheduler from external systems
Date Thu, 09 Oct 2014 21:57:34 GMT
Mayank Bansal created YARN-2670:

             Summary: Adding feedback capability to capacity scheduler from external systems
                 Key: YARN-2670
                 URL: https://issues.apache.org/jira/browse/YARN-2670
             Project: Hadoop YARN
          Issue Type: New Feature
            Reporter: Mayank Bansal
            Assignee: Mayank Bansal

The sheer growth in data volume and Hadoop cluster size make it a significant challenge to
diagnose and locate problems in a production-level cluster environment efficiently and within
a short period of time. Often times, the distributed monitoring systems are not capable of
detecting a problem well in advance when a large-scale Hadoop cluster starts to deteriorate
in performance or becomes unavailable. Thus, incoming workloads, scheduled between the time
when cluster starts to deteriorate and the time when the problem is identified, suffer from
longer execution times. As a result, both reliability and throughput of the cluster reduce
significantly. we address this problem by proposing a system called Astro, which consists
of a predictive model and an extension to the Capacity scheduler. The predictive model in
Astro takes into account a rich set of cluster behavioral information that are collected by
monitoring processes and model them using machine learning algorithms to predict future behavior
of the cluster. The Astro predictive model detects anomalies in the cluster and also identifies
a ranked set of metrics that have contributed the most towards the problem. The Astro scheduler
uses the prediction outcome and the list of metrics to decide whether it needs to move and
reduce workloads from the problematic cluster nodes or to prevent additional workload allocations
to them, in order to improve both throughput and reliability of the cluster.

This JIRA is only for adding feedback capabilities to Capacity Scheduler which can take feedback
from external systems.

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