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ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
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Paper Title: A NOVEL APPROACH FOR MAP REDUCES USING DYNAMIC JOB ORDERING AND SLOT CONFIGURATIONS
Authors Name: RAVI SANKAR KUMAR B , B.B.K PRASAD , Dr. K V SAMBASIVARAO
Unique Id: IJSDR1808024
Published In: Volume 3 Issue 8, August-2018
Abstract: A MapReduce workload generally contains a set of jobs, each of which consists of multiple map tasks followed by multiple reduce tasks. Due to 1) that map tasks can only run in map slots and reduce tasks can only run in reduce slots, and 2) the general execution constraints that map tasks are executed before reduce tasks, different job execution orders and map/reduce slot configurations for a MapReduce workload have significantly different performance and system utilization. This paper proposes two classes of algorithms to minimize the makespan and the total completion time for an offline MapReduce workload. Our first class of algorithms focuses on the job ordering optimization for a MapReduce workload under a given map/reduce slot configuration. In contrast, our second class of algorithms considers the scenario that we can perform optimization for map/reduce slot configuration for a MapReduce workload. We perform simulations as well as experiments on Amazon EC2 and show that our proposed algorithms produce results that are up to 15 _ 80 percent better than currently unoptimized Hadoop, leading to significant reductions in running time in practice.
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Cite Article: "A NOVEL APPROACH FOR MAP REDUCES USING DYNAMIC JOB ORDERING AND SLOT CONFIGURATIONS", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.3, Issue 8, page no.150 - 153, August-2018, Available :http://www.ijsdr.org/papers/IJSDR1808024.pdf
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Publication Details: Published Paper ID: IJSDR1808024
Registration ID:180588
Published In: Volume 3 Issue 8, August-2018
DOI (Digital Object Identifier):
Page No: 150 - 153
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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