In this hands on talk and demonstration I’ll give a very short introduction to stream processing and then dive into writing code and demonstrating the features in Apache Flink that make truly robust stream processing possible. We’ll focus on correctness and robustness in stream processing. During this live demo we’ll be developing a realtime analytics application and modifying it on the fly based on the topics we’re working though. We’ll exercise Flink’s unique features, demonstrate fault-recovery, clearly explain and demonstrate why Event Time is such an important concept in robust stateful stream processing and talk about and demonstrate the features you need in a stream processor in production. Some of the topics covered will be: – Stateful Stream Processing – Event Time vs. Processing Time – Fault tolerance – State management in the face of faults – Savepoints – Data re-processing – Planned downtime and upgrades

Slides: Jamie Grier – Robust Stream Processing with Apache Flink

Video on YouTube


Jamie Grier
Director of Applications Engineering, data Artisans