Coded MapReduce

Songze Li, Mohammad Ali Maddah-Ali, A. Salman Avestimehr

Research output: Chapter in Book/Report/Conference proceedingConference contribution

95 Scopus citations

Abstract

MapReduce is a commonly used framework for executing data-intensive tasks on distributed server clusters. We present Coded MapReduce, a new framework that enables and exploits a particular form of coding to significantly reduce the inter-server communication load of MapReduce. In particular, Coded MapReduce exploits the repetitive mapping of data blocks at different servers to create coded multicasting opportunities in the shuffling phase, cutting down the total communication load by a multiplicative factor that grows linearly with the number of servers in the cluster. We also analyze the tradeoff between the computation load and the communication load of the Coded MapReduce.

Original languageEnglish (US)
Title of host publication2015 53rd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages964-971
Number of pages8
ISBN (Electronic)9781509018239
DOIs
StatePublished - Apr 4 2016
Externally publishedYes
Event53rd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2015 - Monticello, United States
Duration: Sep 29 2015Oct 2 2015

Publication series

Name2015 53rd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2015

Other

Other53rd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2015
Country/TerritoryUnited States
CityMonticello
Period9/29/1510/2/15

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

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