• DocumentCode
    2654397
  • Title

    The Application of MapReduce in the Cloud Computing

  • Author

    Yang, Gaizhen

  • Author_Institution
    Dept. of Math. & Comput. Sci., Huanggang Normal Univ., Huanggang, China
  • fYear
    2011
  • fDate
    22-23 Oct. 2011
  • Firstpage
    154
  • Lastpage
    156
  • Abstract
    Hadoop provides a sophisticated framework for cloud platform programmers, which, MapReduce is a programming model for large-scale data sets of parallel computing. By MapReduce distributed processing framework, we are not only capable of handling large-scale data, and can hide a lot of tedious details, scalability is also wonderful. This paper analyzes the Hadoop architecture and MapReduce Working principle, described how to perform a MapReduce job in the cloud platform, how to write Mapper and Reducer classes, and how to use the object, proposed a program based on the MapReduce framework that enables distributed programming, Comparison results show that use of MapReduce architecture simplifies distributed programming.
  • Keywords
    cloud computing; data handling; parallel programming; software architecture; Hadoop architecture; MapReduce distributed processing framework; MapReduce programming model; MapReduce working principle; cloud computing; cloud platform programmers; distributed programming; large-scale data handling; parallel computing; Cloud computing; Computer architecture; Data models; Distributed databases; File systems; Java; Programming; Hadoop; MapReduce; architecture; cloud platform; distributed programming;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligence Information Processing and Trusted Computing (IPTC), 2011 2nd International Symposium on
  • Conference_Location
    Hubei
  • Print_ISBN
    978-1-4577-1130-5
  • Type

    conf

  • DOI
    10.1109/IPTC.2011.46
  • Filename
    6103560