Stream processing frameworks for big data: the internals

🌊 Navigate the Streams of Big Data with Confidence!

Course Title: Stream Processing Frameworks for Big Data: The Internals

Instructor: Giselle van Dongen

🚀 Course Headline: A deep dive into the internals of Flink, Spark Streaming, Structured Streaming, and Kafka Streams 💧

Course Description:

Are you ready to harness the power of stream processing in your next project but feeling overwhelmed by the plethora of options available? Or perhaps you're aiming to specialize in data engineering and want to build a solid foundation in this pivotal area?

"Stream Processing Frameworks for Big Data: The Internals" is your ultimate guide to understanding the intricacies and nuances of the most popular stream processing frameworks in the industry. By the end of this course, you'll be equipped with a comprehensive knowledge base to select the most suitable framework for your specific needs or embark on an enlightening learning journey.

What You'll Learn:

• Framework Overview: We will provide a detailed explanation and comparison of Flink, Kafka Streams, Spark Streaming, and Structured Streaming.
• Technical Insights: Understand the features, characteristics, and differences that set each framework apart.
• Practical Knowledge: Learn about APIs, latency and throughput performance, scalability, elasticity, fault tolerance, state management, deployment strategies, and more.

Course Structure:

• General Characteristics: What makes each framework stand out?
• APIs: Explore the application programming interfaces of each system.
• Performance Metrics: Analyze latency and throughput performance to understand how these frameworks handle big data streams.
• Scalability & Elasticity: Learn how each framework scales and adapts to varying data volumes.
• Fault Tolerance: Discover mechanisms to ensure your stream processing continues, even under failure scenarios.
• State Management: Understand the different state management approaches and their implications.
• Deployment Considerations: Get insights into deploying these frameworks in a variety of environments.
• ...and much more!

📘 Course Highlights:

• Theoretical Focus: While this course is not a programming one, it delves deeply into the theoretical aspects of stream processing frameworks.
• Real-World Applications: Learn from Giselle's PhD work where these frameworks were benchmarked and analyzed for their characteristics.
• Comprehensive Summary: Conclude with an overview of all the key concepts covered throughout the course.

Why Choose This Course?

This course is meticulously designed to provide you with a robust understanding of the internals of Flink, Kafka Streams, Spark Streaming, and Structured Streaming without getting bogged down in code. By the end, you'll have a clear vision of how these frameworks work under the hood, enabling you to make informed decisions about which one best suits your big data needs.

Join Giselle van Dongen on this educational journey and take the first step towards mastering stream processing for big data! 🎓

Enroll Now to Unlock Your Data Processing Potential! 💫

Note: This course is ideal for data scientists, data engineers, and anyone interested in the theoretical aspects of stream processing frameworks. Prior programming experience with these technologies is beneficial but not required.