Machine Learning for Spark Streaming with StreamDM
Date:
The main goal of this tutorial is to introduce attendees to big data stream mining theory and practice. We will use the StreamDM framework to illustrate concepts and also to demonstrate how data stream mining pipelines can be deployed using StreamDM.
The tools and algorithms in StreamDM are specifically designed for the data stream setting. Due to the large amount of data that is created – and must be processed – in real-time streams, such methods need to be extremely time-efficient while using very small amounts of memory. StreamDM is the first library to include advanced stream mining algorithms for Spark Streaming, and is intended to be the open-source gathering point of the research and implementation of data streams, while designed to allow practical deployments on real-world datasets.