Influence of Hadoop in Big Data Analysis and Its Aspects
Journal Title: International Journal of Modern Engineering Research (IJMER) - Year 2015, Vol 5, Issue 2
Abstract
This paper is an effort to present the basic understanding of BIG DATA and HADOOP and its usefulness to an organization from the performance perspective. Along-with the introduction of BIG DATA, the important parameters and attributes that make this emerging concept attractive to organizations has been highlighted. The paper also evaluates the difference in the challenges faced by a small organization as compared to a medium or large scale operation and therefore the differences in their approach and treatment of BIG DATA. As Hadoop is a Substantial scale, open source programming system committed to adaptable, disseminated, information concentrated processing. A number of application examples of implementation of BIG DATA across industries varying in strategy, product and processes have been presented. This paper also deals with the technology aspects of BIG DATA for its implementation in organizations. Since HADOOP has emerged as a popular tool for BIG DATA implementation. Map reduce is a programming structure for effectively composing requisitions which prepare boundless measures of information (multi-terabyte information sets) in- parallel on extensive bunches of merchandise fittings in a dependable, shortcoming tolerant way. A Map reduce skeleton comprises of two parts. They are “mapper" and "reducer" which have been examined in this paper. The paper deals with the overall architecture of HADOOP along with the details of its various components in Big Data
Authors and Affiliations
Sumaiya Nazneen , Sara Siraj , Tabassum Sultana , Nabeelah Azam , Tayyiba Ambareen , Ethemaad Uddin Ahmed , Mohammed Salman Irshad
Keywords
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