Apache Spark 3 - Real-time Stream Processing using Python
What you'll learn
- Real-time Stream Processing Concepts
- Spark Structured Streaming APIs and Architecture
- Working with File Streams
- Working With Kafka Source and Integrating Spark with Kafka
- State-less and State-full Streaming Transformations
- Windowing Aggregates using Spark Stream
- Watermarking and State Cleanup
- Streaming Joins and Aggregation
- Handling Memory Problems with Streaming Joins
- Creating Arbitrary Streaming Sinks
Course content
- Preview02:58
- Preview01:18
- 00:11Source Code and Other Resources
Requirements
- Spark Fundamentals and exposure to Spark Dataframe APIs
- Kafka Fundamentals and working knowledge of Apache Kafka
- Programming Knowledge Using Python Programming Language
- A Recent 64-bit Windows/Mac/Linux Machine with 8 GB RAM
Description
About the Course
I am creating Apache Spark 3 - Real-time Stream Processing using the Python course to help you understand the Real-time Stream processing using Apache Spark and apply that knowledge to build real-time stream processing solutions. This course is example-driven and follows a working session like approach. We will be taking a live coding approach and explain all the needed concepts along the way.
Who should take this Course?
I designed this course for software engineers willing to develop a Real-time Stream Processing Pipeline and application using the Apache Spark. I am also creating this course for data architects and data engineers who are responsible for designing and building the organization’s data-centric infrastructure. Another group of people is the managers and architects who do not directly work with Spark implementation. Still, they work with the people who implement Apache Spark at the ground level.
Spark Version used in the Course
This Course is using the Apache Spark 3.x. I have tested all the source code and examples used in this Course on Apache Spark 3.0.0 open-source distribution.
Who this course is for:
- Software Engineers and Architects who are willing to design and develop a Bigdata Engineering Projects using Apache Spark
- Programmers and developers who are aspiring to grow and learn Data Engineering using Apache Spark
Instructors
![Prashant Kumar Pandey](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 4.6 Instructor Rating
- 4,542 Reviews
- 34,863 Students
- 8 Courses
Prashant Kumar Pandey is passionate about helping people to learn and grow in their career by bridging the gap between their existing and required skills. In his quest to fulfill this mission, he is authoring books, publishing technical articles, and creating training videos to help IT professionals and students succeed in the industry.
With over 18 years of experience in IT as a developer, architect, consultant, trainer, and mentor, he has worked with international software services organizations on various data-centric and Bigdata projects.
Prashant is a firm believer in lifelong continuous learning and skill development. To popularize the importance of lifelong continuous learning, he started publishing free training videos on his YouTube channel and conceptualized the idea of creating a Journal of his learning under the banner of Learning Journal.
He is the founder, lead author, and chief editor of the Learning Journal portal that offers various skill development courses, training, and technical articles since the beginning of the year 2018.
- 4.6 Instructor Rating
- 4,542 Reviews
- 34,863 Students
- 8 Courses
Learning Journal is a small team of people passionate about helping others learn and grow in their careers by bridging the gap between their existing and required skills. In our quest to fulfill this mission, we are authoring books, publishing technical articles, and creating training videos to help IT professionals and students succeed in the industry.
Together we have over 40+ years of experience in IT as a developer, architect, consultant, trainer, and mentor. We have worked with international software services organizations on various data-centric and Bigdata projects.
Learning Journal is a team of firm believers in lifelong continuous learning and skill development. To popularize the importance of lifelong continuous learning, we started publishing free training videos on our YouTube channel. We conceptualized the notion of continuous learning, creating a journal of our learning under the Learning Journal banner.
We authored various skill development courses, training, and technical articles since the beginning of the year 2018.