• DocumentCode
    1960302
  • Title

    Power Grid Time Series Data Analysis with Pig on a Hadoop Cluster Compared to Multi Core Systems

  • Author

    Bach, F. ; Cakmak, H.K. ; Maass, H. ; Kuehnapfel, U.

  • Author_Institution
    Inst. for Appl. Comput. Sci., Karlsruhe Inst. of Technol., Karlsruhe, Germany
  • fYear
    2013
  • fDate
    Feb. 27 2013-March 1 2013
  • Firstpage
    208
  • Lastpage
    212
  • Abstract
    In order to understand the dependencies in the power system we try to derive state information by combining high-rate voltage time series captures at different locations together with data analysis at different scales. This may enable large-scale simulation and modeling of the grid. Data captured by our recently introduced Electrical Data Recorders (EDR) and power grid simulation data are stored in the large scale data facility (LSDF) at Karlsruhe Institute of Technology (KIT) and growing rapidly in size. In this article we compare classic sequential multithreaded time series data processing to a distributed processing using Pig on a Hadoop cluster. Further we present our ideas for a better organization for our raw- and metadata that is indexable, searchable and suitable for big data.
  • Keywords
    data analysis; meta data; multi-threading; multiprocessing systems; power engineering computing; power grids; time series; EDR; Hadoop cluster; Karlsruhe Institute of Technology; LSDF; distributed processing; electrical data recorders; high-rate voltage time series; large scale data facility; large-scale simulation; metadata; multi core systems; multithreaded time series data processing; power grid simulation data; power grid time series data analysis; Data models; Data visualization; Java; Phasor measurement units; Power grids; Time series analysis; Voltage measurement; Hadoop; LSDF; Pig; Power system; big data; data analysis; multicore; time series;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel, Distributed and Network-Based Processing (PDP), 2013 21st Euromicro International Conference on
  • Conference_Location
    Belfast
  • ISSN
    1066-6192
  • Print_ISBN
    978-1-4673-5321-2
  • Electronic_ISBN
    1066-6192
  • Type

    conf

  • DOI
    10.1109/PDP.2013.37
  • Filename
    6498554