• DocumentCode
    592818
  • Title

    Stream processing with BigData: SSS-MapReduce

  • Author

    Nakada, Hidemoto ; Ogawa, Hiroyo ; Kudoh, T.

  • Author_Institution
    Nat. Inst. of Adv. Ind. Sci. & Technol., Tsukuba, Japan
  • fYear
    2012
  • fDate
    3-6 Dec. 2012
  • Firstpage
    618
  • Lastpage
    621
  • Abstract
    We propose a Map Reduce based stream processing system, called SSS, which is capable of processing stream along with large scale static data. Unlike the existing stream processing systems that can work only on the relatively small on-memory data-set, SSS can process incoming streamed data consulting the stored data. SSS processes streamed data with continuous Mappers and Reducers, which are periodically invoked by the system. It also supports merge operation on two sets of data, which enables stream data processing with large static data. This poster shows overview of SSS stream processing and preliminary evaluation results.
  • Keywords
    distributed processing; merging; BigData; Mappers; Reducer; SSS-MapReduce based stream processing system; data merge operation; large scale static data; on-memory data-set; Cloud computing; Conferences; Data processing; Databases; Servers; Throughput; USA Councils;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cloud Computing Technology and Science (CloudCom), 2012 IEEE 4th International Conference on
  • Conference_Location
    Taipei
  • Print_ISBN
    978-1-4673-4511-8
  • Electronic_ISBN
    978-1-4673-4509-5
  • Type

    conf

  • DOI
    10.1109/CloudCom.2012.6427499
  • Filename
    6427499