Big Data Analytics : Use of Hadoop Mapreduce
Abstract
Big Data is a huge collection of data that comprises both structured data found in traditional databases and unstructured data like text documents, video and audio. Big Data is not merely data but also a collection of various tools, techniques, frameworks and platforms.. Different sources and the system at various rates are used to generate the data’s approach. HADOOP is the popular tool for implementing BIG DATA. HADOOP is an open source technology that enables the distributing process of large data sets of fault tolerance with a very high degree. This paper deals with the technology aspects of BIG DATA for its implementation in organizations by using HADOOP Map Reduce technique.
References
Bernice Purcell (2013) The emergence of “big data” technology and analytics.
Kosha Kothari, Ompriya Kale (2014) Survey of various Clustering Techniques for Big Data in Data Mining. 1(7).
P. Etikala, A. Sultana, M. Schmidt, G. D. Beche, D. Guster (2015) Using Hadoop to Support Big Data Analysis: Security Concerns and Ramifications.
J. Dean, S. Ghemawat (2004) MapReduce: Simplified Data Processing on Large Clusters. 137-150.
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