Apache Flink Documentation

This documentation is for an out-of-date version of Apache Flink. We recommend you use the latest stable version.

This documentation is for Apache Flink version 1.10. These pages were built at: 02/02/22, 11:53:47 AM UTC.

Apache Flink is an open source platform for distributed stream and batch data processing. Flink’s core is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations over data streams. Flink builds batch processing on top of the streaming engine, overlaying native iteration support, managed memory, and program optimization.

First Steps

Code Walkthroughs: Follow step-by-step guides and implement a simple application or query in one of Flink’s APIs.
- Implement a DataStream application
- Write a Table API query
Docker Playgrounds: Set up a sandboxed Flink environment in just a few minutes to explore and play with Flink.
- Run and manage Flink streaming applications
Tutorials: Install Flink on your local machine.
- Setup a local Flink cluster
Concepts: Learn about Flink’s basic concepts to better understand the documentation.

API References

The API references list and explain all features of Flink’s APIs.

Deployment

Before putting your Flink job into production, read the Production Readiness Checklist.

Release Notes

Release notes cover important changes between Flink versions. Please carefully read these notes if you plan to upgrade your Flink setup to a later version.

External Resources

Flink Forward: Talks from past conferences are available at the Flink Forward website and on YouTube. Robust Stream Processing with Apache Flink is a good place to start.
Training: The training materials from Ververica include slides, exercises, and sample solutions.
Blogs: The Apache Flink and Ververica blogs publish frequent, in-depth technical articles about Flink.