This research paper details Apache Flink, an open-source system unifying stream and batch data processing. Flink uses a dataflow model to handle various data processing needs, including real-time analytics and batch jobs, within a single engine. The paper explores Flink's architecture, APIs (including DataStream and DataSet APIs), and fault-tolerance mechanisms such as asynchronous barrier snapshotting. Key features highlighted include flexible windowing, support for iterative dataflows, and query optimization techniques. Finally, the paper compares Flink to other existing systems for batch and stream processing, emphasizing its unique capabilities.

https://asterios.katsifodimos.com/assets/publications/flink-deb.pdf