A Survey of Machine Learning Techniques for Self-tuning Hadoop Performance

Citation

Rahman, Md. Armanur and Hossen, Md. Jakir and Venkataseshaiah, Chinthakunta and Ho, Chin Kuan and Tan, Kim Geok and Sultana, Aziza and Mohd Zebaral Hoque, Jesmeen and Hossain, Ferdous (2018) A Survey of Machine Learning Techniques for Self-tuning Hadoop Performance. International Journal of Electrical and Computer Engineering (IJECE), 8 (3). p. 1854. ISSN 2088-8708

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Abstract

The Apache Hadoop framework is an open source implementation of MapReduce for processing and storing big data. However, to get the best performance from this is a big challenge because of its large number configuration parameters. In this paper, the concept of critical issues of Hadoop system, big data and machine learning have been highlighted and an analysis of some machine learning techniques applied so far, for improving the Hadoop performance is presented. Then, a promising machine learning technique using deep learning algorithm is proposed for Hadoop system performance improvement.

Item Type: Article
Uncontrolled Keywords: Machine learning, MapReduce, Parameter, Hadoop, HDFS
Subjects: Q Science > Q Science (General) > Q300-390 Cybernetics
Divisions: Faculty of Computing and Informatics (FCI)
Faculty of Engineering and Technology (FET)
Depositing User: Ms Rosnani Abd Wahab
Date Deposited: 11 Nov 2020 12:05
Last Modified: 21 Dec 2020 07:07
URII: http://shdl.mmu.edu.my/id/eprint/7335

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