Invited Speaker Tim Renner Presents on Streaming with Storm, Spark and Kafka

I am very happy to announce Dr. Tim Renner will be speaking on Wednesday Feb. 17th for our group on stream processing with examples in some of the most exciting tools in the space. Read about this talk below as well as Tim's background. Space will be limited, so be sure RSVP.

Thanks to our sponsor Actian for hosting!

What's Tough about Streams

Processing an unbounded sequence of data in real-time presents many difficulties not present in traditional batch-oriented processing methods.Problems that are trivial in the batch world can be quite a bit tougher when presented as a streaming problem.For example, streaming programs are never meant to terminate.Calculations and stateful processing must be handled carefully to ensure consistency and correctness.
In this talk I'll present you with one such problem - computing ad clickthrough rates - and use it to illustrate pitfalls that can arise in streaming data situations.I'll discuss a few streaming systems, with particular emphasis on Apache Storm, Apache Spark Streaming, and Apache Kafka.

Bio: Tim Renner is a data scientist/data engineer in the Big Data and Analytics practice at Intersys. He is a consultant specializing in large-scale data and predictive modeling pipelines, having built projects ranging from real-time data ingestion to time series forecasting. Prior to Intersys, Tim worked as an engineer at ExoAnalytic Solutions on multi-sensor data fusion algorithms for ballistic missile target tracking and classification.He holds a Ph.D. in theoretical physics from Baylor University, where he studied superstring theory and particle physics.By night he enjoys learning new programming languages and exploring how different languages express ideas and solve problems.