Apache Flink® — Stateful Computations over Data Streams
- Event-driven Applications
- Stream & Batch Analytics
- Data Pipelines & ETL
- Exactly-once state consistency
- Event-time processing
- Sophisticated late data handling
- SQL on Stream & Batch Data
- DataStream API & DataSet API
- ProcessFunction (Time & State)
- Flexible deployment
- High-availability setup
- Savepoints
- Scale-out architecture
- Support for very large state
- Incremental checkpointing
- Low latency
- High throughput
- In-Memory computing
- Implementing a custom source connector for Table API and SQL - Part Two
In part one of this tutorial, you learned how to build a custom source connector for Flink. In part two, you will learn how to integrate the connector with a test email inbox through the IMAP protocol and filter out emails using Flink SQL.
- Implementing a Custom Source Connector for Table API and SQL - Part One
Part one of this tutorial will teach you how to build and run a custom source connector to be used with Table API and SQL, two high-level abstractions in Flink. The tutorial comes with a bundled docker-compose setup that lets you easily run the connector. You can then try it out with Flink’s SQL client.
- Stateful Functions 3.1.0 Release Announcement
Stateful Functions is a cross-platform stack for building Stateful Serverless applications, making it radically simpler to develop scalable, consistent, and elastic distributed applications. This new release brings various improvements to the StateFun runtime, a leaner way to specify StateFun module components, and a brand new GoLang SDK!
- Help us stabilize Apache Flink 1.14.0 RC0
Dear Flink Community,
- Apache Flink 1.11.4 Released
The Apache Flink community released the next bugfix version of the Apache Flink 1.11 series.