ApacheCon NA 2015

Streaming data presents new challenges for statistics and machine learning on extremely large data sets. Tools such as Apache Storm, a stream processing framework, can power range of data analytics but lack advanced statistical capabilities. In this talk I will discuss developing streaming algorithms with the flexibility of both Storm and R, a statistical programming language.

I will address the critical issues of why and how to use Storm and R to develop streaming algorithms; in particular I will focus on:
• Streaming algorithms
• Online machine learning algorithms
• Use cases showing how to process hundreds of millions of events a day in (near) real time