DocumentCode
3766091
Title
Coded MapReduce
Author
Songze Li;Mohammad Ali Maddah-Ali;A. Salman Avestimehr
Author_Institution
Department of Electrical Engineering, University of Southern California, United States
fYear
2015
Firstpage
964
Lastpage
971
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.
Keywords
"Servers","Encoding","Electrical engineering","Cache memory","Local area networks","Multicast communication","Programming"
Publisher
ieee
Conference_Titel
Communication, Control, and Computing (Allerton), 2015 53rd Annual Allerton Conference on
Type
conf
DOI
10.1109/ALLERTON.2015.7447112
Filename
7447112
Link To Document