Effective processing of unstructured data using python in Hadoop map reduce

Big Data Processing with Hadoop Map-reduce

The amount of data in our world has been exploding, and analyzing large data sets—so-called big data—will become a key basis of competition, underpinning new waves of productivity growth, innovation, and consumer surplus. The increasing volume and detail of information captured by enterprises, the rise of multimedia, social media, and the Internet of Things will fuel exponential growth in data ...

Performance Enhancement of Big Data Processing in Hadoop Map/reduce

Handling Data Skew in Map Reduce Using Hadoop Libra

There are many efficient tools significantly uses Map Reduce applications that assigns data with their corresponding tasks in parallel and distributed data processing. LIBRA symbolizes the lightweight problems of data skew with input data applications that can overlap map and reduce strategies. This is one of the innovative and accurate distribution methods for intermediate data sampling with n...

Analysing Distributed Big Data through Hadoop Map Reduce

This term paper focuses on how the big data is analysed in a distributed environment through Hadoop Map Reduce. Big Data is same as “small data” but bigger in size. Thus, it is approached in different ways. Storage of Big Data requires analysing the characteristics of data. It can be processed by the employment of Hadoop Map Reduce. Map Reduce is a programming model working parallel for large c...

A Multidisciplinary Approaches of Big Data and Data Science Using Hadoop and Map Reduce

Data Science and Big Data have an important role among the modern science and emerging technology. Infact, we can say that these are the two side of the same coin. Data Science is establishing basic foundations to become a profession. The data science community can follow a road map for how data science can be more useful for various social and commercial sectors. Today we are surrounding by da...