• DocumentCode
    244550
  • Title

    Ophidia: A full software stack for scientific data analytics

  • Author

    Fiore, S. ; D´Anca, Alessandro ; Elia, Donatello ; Palazzo, Cosimo ; Foster, Ian ; Williams, Doug ; Aloisio, Giovanni

  • Author_Institution
    Centro Euro-Mediterraneo sui Cambiamenti Climatici, Lecce, Italy
  • fYear
    2014
  • fDate
    21-25 July 2014
  • Firstpage
    343
  • Lastpage
    350
  • Abstract
    The Ophidia project aims to provide a big data analytics platform solution that addresses scientific use cases related to large volumes of multidimensional data. In this work, the Ophidia software infrastructure is discussed in detail, presenting the entire software stack from level-0 (the Ophidia data store) to level-3 (the Ophidia web service front end). In particular, this paper presents the big data cube primitives provided by the Ophidia framework, discussing in detail the most relevant and available data cube manipulation operators. These primitives represent the proper foundations to build more complex data cube operators like the apex one presented in this paper. A massive data reduction experiment on a 1TB climate dataset is also presented to demonstrate the apex workflow in the context of the proposed framework.
  • Keywords
    Big Data; Web services; data analysis; data reduction; Ophidia Web service front end; Ophidia data store; Ophidia software infrastructure; big data analytics platform; big data cube primitives; data reduction; scientific data analytics; software stack; Arrays; Big data; Data models; Meteorology; Servers; Web services; big data; data analytics; multidimensional data; scientific workflow; software infrastructure;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    High Performance Computing & Simulation (HPCS), 2014 International Conference on
  • Conference_Location
    Bologna
  • Print_ISBN
    978-1-4799-5312-7
  • Type

    conf

  • DOI
    10.1109/HPCSim.2014.6903706
  • Filename
    6903706