Data Mining Techniques for Producing Clustering in Big Data with MapReduce Function

被引：0

作者：

Presskila, X. Arogya ^{[1
]}

Robinson, Y. Harold ^{[2
]}

机构：

[1] Department of Computer Science and Engineering, SCAD College of Engineering and Technology, Tirunelveli, India

[2] School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, India

来源：

Studies in Big Data | 2021年 / 93卷

关键词：

Business growth - Clusterings - Data-mining techniques - Google search engine - Heterogeneous sources - Large volumes - Map-reduce - Petabytes;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

Big data is a large collection of dataset from heterogeneous sources of data which may be terabytes or petabytes of data. The big data is useful for existing business growth and also supports to create the new business. Handling this much of data is very difficult in database management system. The problems of big data are storing, processing, analyzing, extracting, and privacy. This survey paper, mainly focused on challenges of big data, how to extract the required data from large volume of data, and also various clustering algorithm. For the extraction of data, mapreduce function is used which is mainly used in Google search engine. © Springer Science and Business Media Deutschland GmbH. All rights reserved.

引用

页码：195 / 203

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