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Data-intensive Systems pp 41–50Cite as

Introduction to MapReduce

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Part of the book series: Advanced Information and Knowledge Processing ((BRIEFSAIKP))

Abstract

This chapter introduces you to MapReduce programming. You will see how functional abstraction lead to real-life implementation. There are two key technical solutions that enable the use of map and reduce functions in practice for parallel processing of big data. First of all, a distributed file system, like Hadoop Distributed File System (HDFS), which ensures delivery of unique subsets of the whole dataset to each map instance.

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Authors and Affiliations

  1. Department of Electrical Engineering and Computer Science, Faculty of Science and Technology, University of Stavanger, Stavanger, Norway

    Tomasz Wiktorski

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  1. Tomasz Wiktorski
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Correspondence to Tomasz Wiktorski .

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Wiktorski, T. (2019). Introduction to MapReduce. In: Data-intensive Systems. Advanced Information and Knowledge Processing(). Springer, Cham. https://doi.org/10.1007/978-3-030-04603-3_5

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  • DOI: https://doi.org/10.1007/978-3-030-04603-3_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-04602-6

  • Online ISBN: 978-3-030-04603-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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