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Analysis of Big Data Using Two Mapper Files in Hadoop
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Author(s): Jyotsna Malhotra (Deaprtment of CSE, Guru Tegh Bahadur Institute of Technology, India), Jasleen Kaur Sethi (USICT, Guru Gobind Singh Indraprastha University, India)and Mamta Mittal (Department of CSE, G. B. Pant Government Engineering College, India)
Copyright: 2021
Volume: 13
Issue: 1
Pages: 9
Source title:
International Journal of Security and Privacy in Pervasive Computing (IJSPPC)
Editor(s)-in-Chief: Tao Gao (Zionlion Group Ltd. Shanghai, China)
DOI: 10.4018/IJSPPC.2021010104
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Abstract
Nowadays, a large amount of valuable uncertain data is easily available in many real-life applications. Many industries and government organizations can exploit this data to extract valuable information. This information can help the managers to enhance their strategies and optimize their plans in making decisions. In fact, various private companies and governments have launched programs with investments and funds in order to maximize profits and optimize resources. This vast amount of data is called big data. The analysis of big data is important for future growth. This paper depicts big data analytics through experimental results. In this paper, data for New York stock exchange has been analyzed using two mapper files in Hadoop. For each year, the calculation of maximum and minimum price of every stock exchange and the average stock price is done.
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