Discover how to build a real-time stream processing pipeline with Apache Fink. Learn about the platform's windowing, event-time processing, and state management features.
Overview
Syllabus
Introduction
- Real-time processing and analytics
- What is Apache Flink?
- Streaming with Apache Flink
- DataStream API
- Related prerequisite courses
- Setting up exercise files
- Setting up the Flink environment
- Reading from a stream source
- Processing streaming data
- Writing to a stream sink
- Using keyed streams
- ProcessFunction
- Splitting a stream
- Merging multiple streams
- Windowing concepts
- Using a Kafka streaming source
- Using sliding windows
- Using session windows
- Window joins
- Time attributes in Flink
- Watermarks
- Setting up event time
- Processing with event time
- Writing to a Kafka sink
- State management in Flink
- Defining states
- Using states
- Advanced state management
- Problem definition
- Computing summary counts
- Computing activity durations
- Next steps
Taught by
Kumaran Ponnambalam
