International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


Downloads: 114 | Views: 181

Research Paper | Computer Science & Engineering | India | Volume 3 Issue 8, August 2014


An Enhanced Approach for Resource Management Optimization in Hadoop

R. Sandeep Raj | G. Prabhakar Raju


Abstract: Many tools and frameworks have been developed to process data on distributed data centers. MapReduce [3] most prominent among such frameworks has emerged as a popular distributed data processing model for processing vast amount of data in parallel on large clusters of commodity machines. The JobTracker in MapReduce framework is responsible for both managing the cluster's resources and executing the MapReduce jobs, a constraint that limits scalability, resource utilization. YARN [2] the next-generation execution layer for Hadoop splits processing and resource management capabilities of JobTracker into separate entities and eliminates the dependency of Hadoop on MapReduce. This new model is more isolated and scalable compared to MapReduce, providing improved features and functionality. This paper discusses the design of YARN and significant advantages over traditional MapReduce.


Keywords: BigData, Hadoop, YARN, MapReduce


Edition: Volume 3 Issue 8, August 2014,


Pages: 1248 - 1253


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