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  Published Paper Details:

  Paper Title

A DYNAMIC MAPREDUCE:SCHEDULING IN LARGE CLUSTERS

  Authors

  Iniyan Senthil Kumar.T,  Poovaraghan.R.J

  Keywords

MapReduce, Hadoop, Cluster, Schedule, heterogeneous workload.

  Abstract


MapReduce is the program model and an association implementation for processing and generating large data sets. User specify a map function that process a key/value pair to generate a set of intermediate key/value pairs and a reduce function that merge all intermediate values associated with the same intermediate key. MapReduce is important Programming model for building data centres containing ten thousands of nodes. In a Practical data, I/O bound jobs and CPU-bounds jobs, which demand different resources, run simultaneously in the same cluster. In this Paper we gives a new view of the MapReduce model and classify the MapReduce workload into three categories based on their CPU and I/O Utilization. We Design a new dynamic MapReduce workload predict mechanism, MR-Predict mechanism, which detect the workload types on the fly. We propose a Triple-Queue scheduler based on the MR-Predict mechanism. The Triple-Queue could improve the usage of both CPU and disk I/O resources under heterogeneous workload.

  IJCRT's Publication Details

  Unique Identification Number - IJPUB1802075

  Paper ID - 181552

  Page Number(s) - 435 - 443

  Pubished in - Volume 6 | Issue 2 | April 2018

  DOI (Digital Object Identifier) -    http://doi.one/10.1729/IJCRT.17539

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Iniyan Senthil Kumar.T,  Poovaraghan.R.J,   "A DYNAMIC MAPREDUCE:SCHEDULING IN LARGE CLUSTERS", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.6, Issue 2, pp.435 - 443, April 2018, Available at :http://www.ijcrt.org/papers/IJPUB1802075.pdf

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ISSN: 2320-2882
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ISSN and 7.97 Impact Factor Details


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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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