Presentation: Patterns of Streaming Applications
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Abstract
Stream processing engines are becoming pivotal in analyzing data. They have evolved beyond a data transport and simple processing machinery, to one that's capable of complex processing. The necessary features and building blocks of these engines are well known. And most capable engines have a familiar Dataflow based programming model.
As with any new paradigm, building streaming applications requires a different mindset and approach. Hence there is a need for identifying and describing patterns and anti-patterns for building these applications. Currently this mindshare is scarce.
Drawn from my experience working with several engineers within and outside of Netflix, this talk will present the following:
- A blueprint for streaming data architectures and a review of desirable features of a streaming engine
- Streaming Application patterns and anti-patterns
- Use cases and concrete examples using Flink
Attendees will come away with patterns that can be applied to any capable stream processing framework such as Apache Flink.
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