International Journal of Computer
Trends and Technology

Research Article | Open Access | Download PDF

Volume 47 | Number 1 | Year 2017 | Article Id. IJCTT-V47P112 | DOI : https://doi.org/10.14445/22312803/IJCTT-V47P112

Big Data Analytics: Map Reduce Function

S.Swarnalatha, K.Vidya

Citation :

S.Swarnalatha, K.Vidya, "Big Data Analytics: Map Reduce Function," International Journal of Computer Trends and Technology (IJCTT), vol. 47, no. 1, pp. 91-94, 2017. Crossref, https://doi.org/10.14445/22312803/IJCTT-V47P112

Abstract

Big data often refers simply to the use of predictive analytics, user behavior analytics, or certain other advanced data analytics methods that extract value from data, and seldom to a particular size of data set. Big data analytics is the process of examining large and varied data sets i.e., big data -- to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful information that can help organizations make moreinformed business decisions. The utilization of Big Data Analytics after integrating it with digital capabilities to secure business growth and its visualization to make it comprehensible to the technically apprenticed business analyzers. Analyzing big data is a very challenging problem today, for such applications; the Map Reduce framework has recently attracted a lot of attention. Google’s Map Reduce or its open-source equivalent Hadoop is a powerful tool for building such applications. In this paper, we explained Map Reduce function with sample data.

Keywords

Map Reduce, Big Data, Data Set.

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