StreamDM: Advanced Data Mining in Spark Streaming

Albert Bifet 1 Silviu Maniu 2 Jianfeng Qian 3 Guangjian Tian 3 Cheng He 3 Wei Fan 4
1 DBWeb
LTCI - Laboratoire Traitement et Communication de l'Information
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 .
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Communication dans un congrès
International Conference on Data Mining Workshops (ICDMW), Nov 2015, Atlantic City, NJ, United States. 2015, 〈10.1109/ICDMW.2015.140〉
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Albert Bifet, Silviu Maniu, Jianfeng Qian, Guangjian Tian, Cheng He, et al.. StreamDM: Advanced Data Mining in Spark Streaming. International Conference on Data Mining Workshops (ICDMW), Nov 2015, Atlantic City, NJ, United States. 2015, 〈10.1109/ICDMW.2015.140〉. 〈hal-01270606〉

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