In this talk, we present Apache SAMOA, an open-source platform for mining big data streams with Apache Flink. Real time analytics is becoming the fastest and most efficient way to obtain useful knowledge from what is happening now. It helps organizations to react quickly when problems appear, and to discover new trends that can point out new business opportunities.
Apache SAMOA includes algorithms for the most common machine learning tasks such as classification, regression and clustering. It provides a pluggable architecture that allows it to run on Apache Flink, but also with other several distributed stream processing engines such as Storm and Samza.
About the speaker
Senior Researcher at Huawei. He is the author of a book on Adaptive Stream Mining and Pattern Learning and Mining from Evolving Data Streams. His main research interest is in Learning from Data Streams. He published more than 60 articles.
He is serving as Industrial Track co-Chair of ECM-PKDD 2015. He is one of the leaders of MOA and Apache SAMOA software environments for implementing algorithms and running experiments for online learning from evolving data streams.
He has been Co-Chair of BigMine (2015, 2014, 2013, 2012), and ACM SAC Data Streams Track (2016, 2015, 2014, 2013, 2012).