Apache Spark 3 & Big Data Essentials in Scala
Apache Spark 3 & Big Data Essentials in Scala, available at $39.99, has an average rating of 4.66, with 25 lectures, based on 2202 reviews, and has 13193 subscribers.
You will learn about 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 This course is ideal for individuals who are Future data scientists or Programmers getting into the field of Big Data or Engineers wanting to learn Spark in Scala, its native language It is particularly useful for Future data scientists or Programmers getting into the field of Big Data or Engineers wanting to learn Spark in Scala, its native language.
Enroll now: Apache Spark 3 & Big Data Essentials in Scala
Summary
Title: Apache Spark 3 & Big Data Essentials in Scala
Price: $39.99
Average Rating: 4.66
Number of Lectures: 25
Number of Published Lectures: 25
Number of Curriculum Items: 25
Number of Published Curriculum Objects: 25
Original Price: $39.99
Quality Status: approved
Status: Live
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
Who Should Attend
- Future data scientists
- Programmers getting into the field of Big Data
- Engineers wanting to learn Spark in Scala, its native language
Target Audiences
- Future data scientists
- Programmers getting into the field of Big Data
- Engineers wanting to learn Spark in Scala, its native language
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:
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it’s blazing fast for big data
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its demand has exploded
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it’s a highly marketable skill
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it’s well maintained, with dozens of high-quality extensions
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it’s a foundation for a data scientist
I like to get to the point and get things done. This course
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deconstructs all concepts into the critical pieces you need
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selects the most important ideas and separates them into what’s simple but critical and what’s powerful
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sequences ideas in a way that “clicks” and makes sense throughout the process of learning
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applies everything in live code
The end benefits are still much greater:
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a completely new mental model around data processing
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significantly more marketable resume
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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
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you’ve never written Scala code before
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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!
Course Curriculum
Chapter 1: Welcome
Lecture 1: Welcome!
Lecture 2: How to Make the Best out of This Course
Lecture 3: Scala Recap
Lecture 4: Spark First Principles
Chapter 2: Spark Structured API: DataFrames
Lecture 1: DataFrames Basics
Lecture 2: DataFrames Basics: Exercises
Lecture 3: How DataFrames Work
Lecture 4: Data Sources
Lecture 5: Data Sources, Part 2 + Exercises
Lecture 6: DataFrames Columns & Expressions
Lecture 7: Columns & Expressions: Exercise
Lecture 8: DataFrame Aggregations
Lecture 9: DataFrame Joins
Lecture 10: DataFrame Joins: Exercise
Chapter 3: Spark Types and Datasets
Lecture 1: Working with Common Spark Data Types
Lecture 2: Working with Complex Spark Data Types
Lecture 3: Managing Nulls in Data
Lecture 4: Type-Safe Data Processing: Datasets
Lecture 5: Datasets, Part 2 + Exercise
Chapter 4: Spark SQL
Lecture 1: Spark as a "Database" with Spark SQL Shell
Lecture 2: Spark SQL
Lecture 3: Spark SQL: Exercises
Chapter 5: Low-Level Spark
Lecture 1: RDDs
Lecture 2: RDDs, Part 2 + Exercise
Chapter 6: Epilogue
Lecture 1: You Rock!
Instructors
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Daniel Ciocîrlan
Software Engineer & Best-Selling Instructor
Rating Distribution
- 1 stars: 3 votes
- 2 stars: 7 votes
- 3 stars: 123 votes
- 4 stars: 655 votes
- 5 stars: 1414 votes
Frequently Asked Questions
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You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
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