MapReduce Foundation of Big Data With Hadoop Environment

Abstract

Hadoop Distributed File System that is also known as HDFS and Hadoop MapReduce are good enough to point out about big data’s consequences in market. This is very positive hints for data scientists. The opposite hints are that person actually be a digger to be able to find the particular from these results. For more accurate result we have to find more possibilities and produce larger number of pair to find greater accuracy. From our past and because of our great future hand, modules which are open source and also company programmers into the whole market have been created and try that modules to increase the adaptability and use of Hadoop environment. And that’s why for this hadoop environment, the adaptability of this map and reduce functionality is in larger cap or we can say that we can get more accurate result with this map and reduce functionality. In Apache project, many developers ware practicing on signals of the hadoop ecosystem. This constant development in working in sequel of static and incremental leads to handle the hadoop ecosystem ahead in a secure and controlled environment. In this paper we demonstrate all these fundamental criterion with example and prove the basic importance of mapreduce foundation with hadoop environment in big data.