Course Outline
Day 1: Course Outline
• Introduction to data streaming principles
• Fundamentals of batch vs. real-time processing
• Basics of event-driven architecture
• Typical industry applications
• Survey of the streaming ecosystem
Day 2
• Design patterns for streaming architectures
• Essentials of distributed messaging systems
• Producers and consumers
• Topics, partitions, and data movement
• Strategies for data ingestion
Day 3
• Concepts and frameworks for stream processing
• Event time vs. processing time
• Windowing methods and practical applications
• Stateful stream processing
• Fundamentals of fault tolerance and checkpointing
Day 4
• Data transformation within streaming pipelines
• ETL and ELT in real-time systems
• Schema management and evolution
• Stream joins and data enrichment
• Introduction to cloud-based streaming services
Day 5
• Monitoring and observability in streaming environments
• Security and access control fundamentals
• Performance tuning and optimization
• Review of end-to-end pipeline design
• Practical scenarios such as fraud detection and IoT processing
Testimonials (2)
A journey through the Spark world: a very intense course. DSL, spark sql, partitioning vs bucketing for me.
Georgiana Elisabeta
Course - Apache Spark Fundamentals
Hands on exercises. Class should have been 5 days, but the 3 days helped to clear up a lot of questions that I had from working with NiFi already
