• 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