Welcome to the InfoSci Platform
Reference Hub1
MapReduce and Hadoop

MapReduce and Hadoop

Luis Rodero-Merino, Gilles Fedak
Copyright: © 2012 |Pages: 19
ISBN13: 9781466600980|ISBN10: 1466600985|EISBN13: 9781466600997
DOI: 10.4018/978-1-4666-0098-0.ch010
Cite Chapter Cite Chapter

MLA

Rodero-Merino, Luis, and Gilles Fedak. "MapReduce and Hadoop." Open Source Cloud Computing Systems: Practices and Paradigms, edited by Luis M. Vaquero, et al., IGI Global, 2012, pp. 197-215. https://doi.org/10.4018/978-1-4666-0098-0.ch010

APA

Rodero-Merino, L. & Fedak, G. (2012). MapReduce and Hadoop. In L. Vaquero, J. Cáceres, & J. Hierro (Eds.), Open Source Cloud Computing Systems: Practices and Paradigms (pp. 197-215). IGI Global. https://doi.org/10.4018/978-1-4666-0098-0.ch010

Chicago

Rodero-Merino, Luis, and Gilles Fedak. "MapReduce and Hadoop." In Open Source Cloud Computing Systems: Practices and Paradigms, edited by Luis M. Vaquero, Juan Cáceres, and Juan J. Hierro, 197-215. Hershey, PA: IGI Global, 2012. https://doi.org/10.4018/978-1-4666-0098-0.ch010

Export Reference

Mendeley
Favorite

Abstract

This chapter introduces the MapReduce solution for distributed computation. It explains the fundamentals of MapReduce and describes in which scenarios it can be applied (basically, processing of massive data by easily parallelizable algorithms). Also, this chapter gives an overview of the open source project Hadoop, an implementation of MapReduce. Its architecture is depicted, and an easy step-by-step guide to install Hadoop is included, along with programming examples of how to use Hadoop.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.