Need and Challenges of Stream Processing | Course in Spark Structured Streaming 3.0 | Lesson 1

Full Course is available here:
https://www.udemy.com/course/apache-s...
https://www.udemy.com/course/spark-st...

Getting faster action from the data is the need of many industries and Stream Processing helps doing just that. But it comes with its own set of theories, challenges and best practices.

Apache Spark has seen tremendous development being in stream processing. The rich features of Spark Structured Streaming introduces a learning curve and this course is aimed at bringing all those concepts in a friendly and easy to reflect manner.

You will learn the differences between batch & stream processing and the challenges specific to stream processing. Quickly we'll move to understand the concepts of stream processing with wide varieties of examples & hands-on, dealing with inner working and taking a use case towards the end. All of this activity will be on cloud using Spark 3.0.

What you’ll learn
In Depth exploration of Spark Structured Streaming 3.0
Are there any course requirements or prerequisites?
Understanding of Spark SQL and Python (or pyspark)
Who this course is for:
Data Engineers looking to expand their skill set, Data Scientists who wish want hands on working with stream processing and Technical Architects who want to evaluate the Spark Structured Streaming for their use cases

Slides: https://drive.google.com/drive/folder...
Codes: https://drive.google.com/drive/folder...