New Pluralsight Course: PySpark Streaming
I’ve been quite busy last few months working on a new Pluralsight course and re-evaluating other things in general. And now that the course is finally published, I can share it with you all! The course is titled Real-time Stream Processing with PySpark and it’s available on Pluralsight. In this course, I cover the basics of stream processing with PySpark, including how to set up a streaming application, process data in real-time, and handle common challenges such as fault tolerance and state management.
The course is designed for developers and data engineers who are familiar with PySpark and want to learn how to build real-time streaming applications. It covers the following topics:
- Introduction to stream processing and PySpark.
- Setting up a PySpark streaming application.
- Processing data in real-time using PySpark.
- Handling common challenges in stream processing, such as fault tolerance and state management.
- Best practices for building real-time streaming applications with PySpark.
- Real-world examples and use cases of PySpark streaming.
- Tips and tricks for optimizing PySpark streaming applications.
- Conclusion and next steps for learning more about PySpark streaming.
The course is structured in a way that allows you to learn at your own pace, with hands-on exercises and real-world examples to help you apply what you’ve learned. By the end of the course, you’ll have a solid understanding of how to build real-time streaming applications with PySpark and be able to apply these skills in your own projects.
I had a lot of fun creating this course and I hope you find it helpful.
To contact me, send an email anytime or leave a comment below.