Hadoop Mapreduce Framework in Big Data Analytics
 | International Journal of ComputerTrends and Technology (IJCTT) |  |
| © 2014 by IJCTT Journal | ||
| Volume-8 Number-3 | ||
| Year of Publication : 2014 | ||
| Authors : Vidyullatha Pellakuri , Dr.D. Rajeswara Rao | ||
| DOI : 10.14445/22312803/IJCTT-V8P121 |
Vidyullatha Pellakuri , Dr.D. Rajeswara Rao. "Hadoop Mapreduce Framework in Big Data Analytics". International Journal of Computer Trends and Technology (IJCTT) V8(3):115-119, February 2014. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract -
As Hadoop is a Substantial scale, open source programming system committed to adaptable, disseminated, information concentrated processing. Hadoop [1] Mapreduce is a programming structure for effectively composing requisitions which prepare boundless measures of information (multi-terabyte information sets) in-parallel on extensive bunches (many hubs) of merchandise fittings in a dependable, shortcoming tolerant way. A Mapreduce [6] skeleton comprises of two parts. They are "mapper" and "reducer" which have been examined in this paper. Fundamentally this paper keeps tabs on Mapreduce modifying model, planning undertakings, overseeing and re-execution of the fizzled assignments. Workflow of Mapreduce is indicated in this exchange.
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Keywords
Framework, HDFS, Mapreduce, Shuffle, Workflow.