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Apache Spark 3 & Big Data Essentials in Scala | Rock the JVM
Learn Spark 3: Learn practical Big Data with Spark DataFrames, Datasets, RDDs and Spark SQL, hands-on, in Scala
Created by Daniel Ciocîrlan, offered on Udemy
To make sure that we score courses properly, we pay a lot of attention to the reviews students leave on courses and how many students are taking a course in the first place. This course has a total of 8437 students which left 1428 reviews at an average rating of 4.61. Impressive!
We analyze course length to see if courses cover all important aspects of a topic, taking into account how long the course is compared to the category average. This course has a length of 7 hours 18 minutes, which is pretty short. This might not be a bad thing, but we've found that longer courses are often more detailed & comprehensive. The average course length for this entire category is 4 hours 58 minutes.
This course currently has a bestcourses score of 8.0/10, which makes it a great course to learn from. On our entire platform, only 15% of courses achieve this rating!
UPDATED FOR SPARK 3.2
In this course, we will learn how to write big data applications with Apache Spark 3 and Scala. You'll write 2000+ lines of Spark code yourself, with guidance, and you will become a rockstar.
This course is for Scala programmers who are getting started with Apache Spark and big data. The course is not for advanced Spark engineers.
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 processing
significantly more marketable resume
more enjoyable work - Spark is fun!
This course is for established programmers with experience with Scala and with functional programming at the level of the Rock the JVM Scala beginners course. I already assume a solid understanding of general programming fundamentals.
This course is NOT for you if
you've never written Scala 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!
What you will learn
- apply Spark big data principles
- practice Spark DataFrames operations with 100+ examples and exercises
- practice type-safe data processing with Spark Datasets
- work with low-level Spark APIs with RDDs
- use Spark SQL for data processing
- migrate data from various data sources, including databases
- Scala fundamentals, at the level of the Rock the JVM beginners course
- Scala advanced - implicits