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 :
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