Get started with Apache Flink, the open source framework that powers some of the world’s largest stream processing applications. With this practical book, you’ll explore the fundamental concepts of parallel stream processing and discover how this technology differs from traditional batch data processing.
Longtime Apache Flink committers Fabian Hueske and Vasia Kalavri show you how to implement scalable streaming applications with Flink’s DataStream API and continuously run and maintain these applications in operational environments. Stream processing is ideal for many use cases, including low-latency ETL, streaming analytics, and real-time dashboards as well as fraud detection, anomaly detection, and alerting. You can process continuous data of any kind, including user interactions, financial transactions, and IoT data, as soon as you generate them.
- Learn concepts and challenges of distributed stateful stream processing
- Explore Flink’s system architecture, including its event-time processing mode and fault-tolerance model
- Understand the fundamentals and building blocks of the DataStream API, including its time-based and statefuloperators
- Read data from and write data to external systems with exactly-once consistency
- Deploy and configure Flink clusters
- Operate continuously running streaming applications
About the Author
Fabian Hueske is involved with Apache Flink since its very beginnings in 2009 as a research project called Stratosphere at TU Berlin. He is one of the three initial authors of the system and worked on it as part of his PhD research. Fabian is one of the initial committers and a PMC member of Apache Flink. He is a co-founder of data Artisans, a Berlin-based start-up devoted to foster Flink, where he works as a software engineer and contributes to Apache Flink. Vasiliki Kalavri is a PhD student at KTH, Stockholm, and UCL, Belgium, and an EMJD-DC fellow. She does research in distributed data processing and large-scale graph analysis.She is a committer and PMC member of Apache Flink, focusing her efforts on its graph processing library and API, Gelly.
