• DocumentCode
    3739355
  • Title

    StreamDM: Advanced Data Mining in Spark Streaming

  • Author

    Albert Bifet;Silviu Maniu;Jianfeng Qian;Guangjian Tian;Cheng He;Wei Fan

  • Author_Institution
    Telecom ParisTech, Paris, France
  • fYear
    2015
  • Firstpage
    1608
  • Lastpage
    1611
  • Abstract
    Real-time analytics are becoming increasingly important due to the large amount of data that is being created continuously. Drawing from our experiences at Huawei Noah´s Ark Lab, we present and demonstrate here StreamDM, a new open source data mining and machine learning library, designed on top of Spark Streaming, an extension of the core Spark API that enables scalable stream processing of data streams. StreamDM is designed to be easily extended and used, either practitioners, developers, or researchers, and is the first library to contain advanced stream mining algorithms for Spark Streaming.
  • Keywords
    "Sparks","Data mining","Libraries","Training","Algorithm design and analysis","Machine learning algorithms","Data structures"
  • Publisher
    ieee
  • Conference_Titel
    Data Mining Workshop (ICDMW), 2015 IEEE International Conference on
  • Electronic_ISBN
    2375-9259
  • Type

    conf

  • DOI
    10.1109/ICDMW.2015.140
  • Filename
    7395869