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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
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Content

Platform: Udemy
Video: 7h 12m
Language: English
Next start: On Demand

Table of contents

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!

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

Requirements

• Scala and functional programming essentials, at the level of the beginners course (implicits are a plus)
• Spark fundamentals, including Spark SQL, DataFrames and RDDs
• Good general knowledge of parallel/distributed systems (nodes, threads, etc)

This course is for

• Scala & Spark programmers who need to set up data pipelines in real time
• Data scientists who need to work with streaming data
Software Engineer & Best-Selling Instructor
I’m a software engineer with a passion for teaching. Big fan of Scala and the JVM.
I have a Master’s Degree in Computer Science and I wrote my Bachelor and Master theses on Quantum Computation. Before starting to learn programming, I won medals at international Physics competitions.
For 7+ years, I’ve taught a variety of Computer Science topics to 30000+ of students at various levels. I’ve held Hour of Code for 7 year-olds, I’ve taught university students who now work at Google and Facebook, I’ve held live trainings for software engineering teams at Adobe and Apple, and I’m now so excited to share what I know with a wider community online.
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Platform: Udemy
Video: 7h 12m
Language: English
Next start: On Demand

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