Data streaming is emerging as a new and increasingly popular architectural pattern for data infrastructure. Data streaming architectures embrace the fact that data in practice is not static but is continuously produced in the form of events. Streaming technology, such as Apache Flink, one of the most popular stream processing frameworks in the Apache Software Foundation, follows this philosophy to the end: applications work directly on the streams of events and on the isolated local state that aggregates the event histories. Among the many disruptive promises of streaming architectures backed by modern streaming systems such as Apache Flink are:
Stephan Ewen and Kostas Tzoumas introduce the data streaming architecture paradigm, outline the building blocks of data streaming applications—including event streams, transformations and windows, different notions of time and how to handle those, and how to keep application state consistent—and show how to build an exemplary set of simple but representative applications using Apache Flink.
Stephan Ewen is one of the originators and committers of the Apache Flink project and CTO at data Artisans, where he leads the development of large-scale data stream processing technology. He is also a PMC member of Apache Beam, a project to create a unified abstraction for Batch and Stream data processing. He coauthored the Stratosphere system and has worked on data processing technologies at IBM and Microsoft. Stephan holds a PhD from the Berlin University of Technology.
Kostas Tzoumas is a PMC member of the Apache Flink project and cofounder of data Artisans, the company founded by the original development team that created Flink. Kostas has spoken extensively about Flink, including at Hadoop Summit San Jose 2015.
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