• DocumentCode
    659571
  • Title

    A big data analytics framework for scientific data management

  • Author

    Fiore, S. ; Palazzo, Cosimo ; D´Anca, Alessandro ; Foster, Ian ; Williams, Dean N. ; Aloisio, Giovanni

  • Author_Institution
    Centro Euro-Mediterraneo sui Cambiamenti Climatici, Italy
  • fYear
    2013
  • fDate
    6-9 Oct. 2013
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    The Ophidia project is a research effort addressing big data analytics requirements, issues, and challenges for eScience. We present here the Ophidia analytics framework, which is responsible for atomically processing, transforming and manipulating array-based data. This framework provides a common way to run on large clusters analytics tasks applied to big datasets. The paper highlights the design principles, algorithm, and most relevant implementation aspects of the Ophidia analytics framework. Some experimental results, related to a couple of data analytics operators in a real cluster environment, are also presented.
  • Keywords
    Big Data; data analysis; natural sciences computing; pattern clustering; Ophidia analytics framework; Ophidia project; array-based data manipulation; array-based data processing; array-based data tranformation; big data analytics framework; cluster analytics task; data analytics operators; eScience; scientific data management; Arrays; Data handling; Information management; Libraries; Meteorology; Servers; big data; data analytics; eScience; parallel I/O;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Big Data, 2013 IEEE International Conference on
  • Conference_Location
    Silicon Valley, CA
  • Type

    conf

  • DOI
    10.1109/BigData.2013.6691720
  • Filename
    6691720