Apache Spark Streaming 3 with Scala | Rock the JVM
Stream big data with Apache Spark Streaming 3 and integrate with Kafka, JDBC, Cassandra and more, hands-on, in Scala
Ratings 4.23 / 5.00
What You Will Learn!
- Process data as it arrives
- Handle data of any scale in real time
- Use Structured Streaming and SQL on streaming data
- Use low-level, high-control APIs with DStreams
- Integrate Spark with Kafka, JDBC, Cassandra
- Master advanced concepts including window functions and watermarking
Description
In this course, we will learn how to stream big data with Apache Spark 3. You'll write 1500+ lines of Spark code yourself, with guidance, and you will become a rockstar.
This course is for Spark & Scala programmers who now need to work with streaming data, or who need to process data in real time.
Why Spark in Scala:
it's blazing fast for big data
its demand has exploded
it's a highly marketable skill
it's well maintained, with dozens of high-quality extensions
it's a foundation for a data scientist
I like to get to the point and get things done. This course
deconstructs all concepts into the critical pieces you need
selects the most important ideas and separates them into what's simple but critical and what's powerful
sequences ideas in a way that "clicks" and makes sense throughout the process of learning
applies everything in live code
The end benefits are still much greater:
a completely new mental model around data streaming
significantly more marketable resume
more enjoyable work - Spark is fun!
This course is for established programmers with experience with both Scala and Spark at least at the level of the Rock the JVM essential courses for Scala and Spark. I already assume a solid understanding of general programming fundamentals.
This course is NOT for you if
you've never written Scala or Spark code before
you don't have some essential parallel programming background (e.g. what's a process/a thread)
The course is comprehensive, but you'll always see me get straight to the point. So make sure you have a good level of focus and commitment to become a badass programmer.
I believe both theory and practice are important. That's why you'll get lectures with code examples, real life code demos and assignments, plus additional resources, instructions, exercises and solutions. At the end of the course, you'll have written thousands of lines of Spark.
I've seen that my students are most successful - and my best students work at Google-class companies - when they're guided, but not being told what to do. I have exercises waiting for you, where I offer my (opinionated) guidance but otherwise freedom to experiment and improve upon your code.
Definitely not least, my students are most successful when they have fun along the way!
So join me in this course and let's rock the JVM!
Who Should Attend!
- Scala & Spark programmers who need to set up data pipelines in real time
- Data scientists who need to work with streaming data
