This course is a hands-on introduction to Apache Flink for Java and Scala developers who want to learn to build streaming applications.

After taking this course you will have learned enough about Flink's core concepts, its DataStream API, and its distributed runtime to be able to develop solutions for a wide variety of use cases, including data pipelines and ETL jobs, streaming analytics, and event-driven applications.

The programming exercises are oriented around common use cases, and will give you a chance to see how the pieces of the API work together to solve real problems.

Schedule:

Monday, June 7, (9am-12pm Pacific Daylight Time, 6-9pm Central European Summer Time)

Tuesday, June 8, (9am-12pm Pacific Daylight Time, 6-9pm Central European Summer Time)

Thursday, June 10, (9am-12pm Pacific Daylight Time, 6-9pm Central European Summer Time)

Course Content

• Introduction to Stream Processing and Apache Flink
• Runtime Architecture
• Foundations of the DataStream API
• Data Pipelines and Stateful Stream Processing
• Event Time and Watermarks
• Process Functions, Side Outputs, and Timers
• Windows and Streaming Analytics
• State Backends
• Fault Tolerance
• Connector Ecosystem
• Application Evolution: Rescaling, Upgrades, State Migration
• Intro to Flink SQL and the Table API
• Use Cases and Application Patterns
• Testing

Prerequisites

No prior knowledge of Apache Flink is required.

For the hands-on exercises you will need a computer with at least 8 GB RAM (MacOS, Linux, or Windows), with these tools installed:

• Git
• Java 8 or 11 JDK (a JRE is not sufficient)
• An IDE for Java (or Scala) development
• Docker

Format

As a remote, instructor-led training, this is delivered as three sessions, each about 3 hours long, with the hands-on exercises assigned as homework to be done outside of class.