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Encyclopedia of Database Systems pp 2206–2210Cite as

MapReduce

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Scientific Fundamentals

MapReduce refers to both a programming model and the corresponding distributed framework. Its model is composed of two phases, map and reduce, which manipulate data formated as key-value pairs. Map phase splits and sorts data on keys, whereas reduce phase applies user-defined function to process data with the same key. In this way, MapReduce is a typical divide-and-conquer framework that is designed to handle embarrassingly parallel problems, namely problems that can be split into sub-tasks with little or no synchronization costs.

Definition

MapReduce is a programming framework that allows users to process large-scaled data by leveraging the parallelism among a cluster of nodes. It is also used to refer to the distributed engine which splits and disseminates users’ jobs and monitors their processing in the cluster. MapReduce is a typical divide-and-conquer framework, since it transforms the user code into an embarrassingly parallel job, where little or no effort...

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Recommended Reading

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Author information

Authors and Affiliations

  1. Zhejiang University, Hangzhou, Zhejiang, People’s Republic of China

    Sai Wu

Authors
  1. Sai Wu
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Correspondence to Sai Wu .

Editor information

Editors and Affiliations

  1. Georgia Institute of Technology College of Computing, Atlanta, GA, USA

    Ling Liu

  2. University of Waterloo School of Computer Science, Waterloo, ON, Canada

    M. Tamer Özsu

Section Editor information

  1. College of Computing, Georgia Institute of Technology, Atlanta, GA, USA

    Ling Liu

  2. Cheriton School of Computer Science, University of Waterloo, Waterloo, Ontario, Canada

    M. Tamer Özsu

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Wu, S. (2018). MapReduce. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_80802

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