research-article

Distributed data management using MapReduce

Authors:

M. Tamer Özsu,

Sai WuAuthors Info & Claims

ACM Computing Surveys (CSUR), Volume 46, Issue 3

Article No.: 31, Pages 1 - 42

https://doi.org/10.1145/2503009

Published: 01 January 2014 Publication History

Abstract

MapReduce is a framework for processing and managing large-scale datasets in a distributed cluster, which has been used for applications such as generating search indexes, document clustering, access log analysis, and various other forms of data analytics. MapReduce adopts a flexible computation model with a simple interface consisting of map and reduce functions whose implementations can be customized by application developers. Since its introduction, a substantial amount of research effort has been directed toward making it more usable and efficient for supporting database-centric operations. In this article, we aim to provide a comprehensive review of a wide range of proposals and systems that focusing fundamentally on the support of distributed data management and processing using the MapReduce framework.

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cover image ACM Computing Surveys

ACM Computing Surveys Volume 46, Issue 3

January 2014

507 pages

ISSN:0360-0300

EISSN:1557-7341

DOI:10.1145/2578702

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Publication History

Published: 01 January 2014

Accepted: 26 June 2013

Revised: 21 February 2013

Received: 15 September 2012

Published in CSUR Volume 46, Issue 3

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