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:

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 

1. deconstructs all concepts into the critical pieces you need

2. selects the most important ideas and separates them into what’s simple but critical and what’s powerful

3. sequences ideas in a way that “clicks” and makes sense throughout the process of learning

4. 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!

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

Daniel Cioc?rlan
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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Can I take my courses with me wherever I go?

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