In this talk Matthias Niehoff will give an overview on various concepts used in data stream processing. Most of them are used for solving problems in the field of time, focussing on processing time compared to event time. The techniques shown are based on the Dataflow API as it was introduced by Google.
The talk will start with an short introduction in the how and why of stream processing, followed by a deep-dive into the dataflow concepts. In the end I will give a brief outline on the implementation status of those strategies in the popular streaming frameworks Apache Spark, Apache Flink and Kafka Streams.
More on this topic can be found in Matthias‘ blog post: https://blog.codecentric.de/2017/03/verteilte-stream-processing-frameworks-fuer-fast-data-big-data-ein-meer-moeglichkeiten/