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An Introduction to Clustering Algorithms in Big Data

An Introduction to Clustering Algorithms in Big Data
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Author(s): Rajit Nair (Jagran Lakecity University, India) and Amit Bhagat (Maulana Azad National Institute of India, India)
Copyright: 2021
Pages: 18
Source title: Encyclopedia of Information Science and Technology, Fifth Edition
Source Author(s)/Editor(s): Mehdi Khosrow-Pour D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-7998-3479-3.ch040

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Abstract

In big data, clustering is the process through which analysis is performed. Since the data is big, it is very difficult to perform clustering approach. Big data is mainly termed as petabytes and zeta bytes of data and high computation cost is needed for the implementation of clusters. In this chapter, the authors show how clustering can be performed on big data and what are the different types of clustering approach. The challenge during clustering approach is to find observations within the time limit. The chapter also covers the possible future path for more advanced clustering algorithms. The chapter will cover single machine clustering and multiple machines clustering, which also includes parallel clustering.

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