E-Books →Stream Processing with Apache Flink Fundamentals, Implementation, and Operation of Streaming Applications

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