Discover how to use Apache Flink and associated technologies to build stream-processing use cases leveraging popular patterns.
Overview
Syllabus
Introduction
- Stream processing with Flink
- What you should know
- What is stream processing?
- Streaming: Opportunities and challenges
- Streaming with Flink
- Setting up the exercise files
- Setting up Kafka
- Setting up MariaDB and Redis
- Streaming analytics: Pattern
- Streaming analytics: Use case design
- Streaming analytics: Helper classes
- Streaming analytics: Pipeline implementation
- Streaming analytics: Results review
- Alerts and thresholds: Pattern
- Alerts and thresholds: Use case design
- Alerts and thresholds: Helper classes
- Alerts and thresholds: Pipeline implementation
- Alerts and thresholds: Review
- Leaderboards: Pattern
- Leaderboards: Use case design
- Leaderboards: Helper classes
- Leaderboards: Pipeline implementation
- Leaderboards: Review
- Real-time predictions: Pattern
- Real-time predictions: Use case design
- Real-time predictions: Helper classes
- Real-time predictions: Pipeline implementation
- Real-time predictions: Review
- Use case definition
- Design of the project
- Code walkthrough
- Execute and analyze
- Next steps
Taught by
Kumaran Ponnambalam