Rate the Article: A Review on Need of MapReduce in Big Data Application, IJSR, Call for Papers, Online Journal
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: 113 | Views: 331

Survey Paper | Computer Science & Engineering | India | Volume 4 Issue 12, December 2015 | Rating: 6.6 / 10


A Review on Need of MapReduce in Big Data Application

Sushant Shirish Nagavkar, Ashishkumar


Abstract: Big-data is broadly distributed data processing applications that operate on large amount of data. The growing power of Big Data assume the significance of analyzing huge amount of data with a frequent and quick rate of growth and change in databases and data warehouses. An inspection of the MapReduce framework is that the framework creates a large amount of transitional data. This survey aims that the modern techniques for parallel query processing using MapReduce. The main fact of data analytics is scalability, due to the huge volume of data that need to be extracted, processed, and analyzed in a sensible fashion. MapReduce is most popular framework for large-scale data analytics mainly due to its salient features like scalability, fault-tolerance, simple programming, and flexibility.


Keywords: BEA, Big-data, Hadoop, HDFS, MapReduce


Edition: Volume 4 Issue 12, December 2015,


Pages: 1290 - 1293



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