• DocumentCode
    267168
  • Title

    R2Time: A Framework to Analyse Open TSDB Time-Series Data in HBase

  • Author

    Agrawal, Bikash ; Chakravorty, Antorweep ; Chunming Rong ; Wlodarczyk, Tomasz Wiktor

  • Author_Institution
    Dept. of Comput. & Electr. Eng., Univ. of Stavanger, Stavanger, Norway
  • fYear
    2014
  • fDate
    15-18 Dec. 2014
  • Firstpage
    970
  • Lastpage
    975
  • Abstract
    In recent years, the amount of time series data generated in different domains have grown consistently. Analyzing large time-series datasets coming from sensor networks, power grids, stock exchanges, social networks and cloud monitoring logs at a massive scale is one of the biggest challenges that data scientists are facing. Big data storage and processing frameworks provides an environment to handle the volume, velocity and frequency attributes associated with time-series data. We propose an efficient and distributed computing framework - R2Time for processing such data in the Hadoop environment. It integrates R with a distributed time-series database (Open TSDB) using a MapReduce programming framework (RHIPE). R2Time allows analysts to work on huge datasets from within a popular, well supported, and powerful analysis environment.
  • Keywords
    Big Data; parallel processing; time series; HBase; Hadoop environment; MapReduce programming framework; OpenTSDB; OpenTSDB time-series data; R2Time; RHIPE; big data processing frameworks; big data storage; data scientists; distributed computing framework; distributed time-series database; frequency attributes; large time-series dataset analysis; velocity attributes; Computational modeling; Data models; Data visualization; Distributed databases; Libraries; Measurement; Programming; HBase; Hadoop; Open TSDB; R; time-series;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cloud Computing Technology and Science (CloudCom), 2014 IEEE 6th International Conference on
  • Conference_Location
    Singapore
  • Type

    conf

  • DOI
    10.1109/CloudCom.2014.84
  • Filename
    7037792