Data Stream Processing Concepts and Implementations by Matthias Niehoff

In this talk I 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 include the Dataflow API as it was introduced by Google and the concepts of stream and table duality. But I will also come up with other problems like data lookup and deployment of streaming applications and various strategies on solving these problems.

In the end I will give a brief outline on the implementation status of those strategies in the popular streaming frameworks Apache Spark Streaming, Apache Flink and Kafka Streams.

Matthias Niehoff is an IT consultant at codecentric AG in Germany, where he focuses on big data and streaming applications with Apache Cassandra and Apache Spark as well as other tools in the area of big data. Matthias shares his experience at conferences, meetups, and user groups.

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