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 :
بازگشت