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Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Big Data Processing on Cloud Computing Using Hadoop Mapreduce and Apache Spark

Big Data Processing on Cloud Computing Using Hadoop Mapreduce and Apache Spark
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Author(s): Yassir Samadi (Mohammed V University, Morocco), Mostapha Zbakh (Mohammed V University, Morocco)and Amine Haouari (Mohammed V University, Morocco)
Copyright: 2021
Pages: 22
Source title: Research Anthology on Architectures, Frameworks, and Integration Strategies for Distributed and Cloud Computing
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-7998-5339-8.ch039

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Abstract

Size of the data used by enterprises has been growing at exponential rates since last few years; handling such huge data from various sources is a challenge for Businesses. In addition, Big Data becomes one of the major areas of research for Cloud Service providers due to a large amount of data produced every day, and the inefficiency of traditional algorithms and technologies to handle these large amounts of data. In order to resolve the aforementioned problems and to meet the increasing demand for high-speed and data-intensive computing, several solutions have been developed by researches and developers. Among these solutions, there are Cloud Computing tools such as Hadoop MapReduce and Apache Spark, which work on the principles of parallel computing. This chapter focuses on how big data processing challenges can be handled by using Cloud Computing frameworks and the importance of using Cloud Computing by businesses

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