A Survey on Parallel Rough Set Based Knowledge Acquisition Using MapReduce from Big Data

نویسنده

  • Sachin Jadhav
چکیده

Nowadays, the volume of data is growing at an nprecedented rate, big data mining , and knowledge discovery have become a new challenge in the era of data mining and machine learning. Rough set theory for knowledge acquisition has been successfully applied in data mining. The MapReduce technique, received more attention from scientific community as well as industry for its applicability in big data analysis. In this paper we have presented working and execution flow of the MapReduce Programming paradigm with Map and Reduce function.This paper also describes the various Mapreduce implementation with their pros and cons such as Google’s MapReduce, ,YARN, Twister, phoenix etc. In this work we have also briefly discussed different issues and challenges that are faced by MapReduce while handling the Big data. And lastly we have presented some advantages of the Mapreduce Prograaming model.

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تاریخ انتشار 2014