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
Link To Document