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This documentation is for an out-of-date version of Apache Flink.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 1.6. These pages were built at: 02/02/22, 11:25:00 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

Concepts: Start with the basic concepts of Flink’s Dataflow Programming Model and Distributed Runtime Environment. This will help you understand other parts of the documentation, including the setup and programming guides. We recommend you read these sections first.
Quickstarts: Run an example program on your local machine or study some examples.
Programming Guides: You can read our guides about basic API concepts and the DataStream API or the DataSet API to learn how to write your first Flink programs.

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 data Artisans include slides, exercises, and sample solutions.
Blogs: The Apache Flink and data Artisans blogs publish frequent, in-depth technical articles about Flink.