Complex event processing (CEP) is the art of detecting patterns (or predefined sequences of data) over continuous streams of data. Use cases can range from searching for DNA sequences and detecting suspicious activity in transaction logs to tracking shipments with specific characteristics (e.g., contaminated goods) and analyzing user activity on websites, and financial institutions, network security companies, retailers, IoT-based services, and many other organizations can benefit (and, in fact, are already benefiting) from implementing a state-of-art CEP library on top of a state-of-the-art stream processor like Apache Flink.
Kostas Kloudas offers an overview of Flink’s CEP library and explains the benefits of its integration with Flink. You’ll learn some of the most interesting features of FlinkCEP and discover how the integration of FlinkCEP with Flink allows the former to take advantage of Flink’s rich ecosystem (e.g., connectors) and its advanced stream processing capabilities, such as support for event-time processing, exactly once state semantics, fault tolerance, savepoints, and high throughput.
Kostas Kloudas is a software engineer at data Artisans and a Flink committer working to make Apache Flink the best open source stream processing engine (and your data’s best friend). Previously, Kostas was a postdoctoral researcher at IST in Lisbon. He holds a PhD in computer science from Inria in France and an engineering diploma from NTUA in Athens, where his main research focus was cloud storage and distributed processing.
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