Udemy - Spark 3.0 & Big Data Essentials with Scala

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Spark 3.0 Big Data Essentials with Scala [TutsNode.com] - Spark 3.0 Big Data Essentials with Scala 2. Spark Structured API DataFrames
  • 8. DataFrame Aggregations.mp4 (250.8 MB)
  • 8. DataFrame Aggregations.srt (30.5 KB)
  • 5. Data Sources, Part 2 + Exercises.srt (30.0 KB)
  • 1. DataFrames Basics.srt (27.5 KB)
  • 7. Columns & Expressions Exercise.srt (18.8 KB)
  • 5. Data Sources, Part 2 + Exercises.mp4 (240.1 MB)
  • 10. DataFrame Joins Exercise.srt (19.3 KB)
  • 4. Data Sources.srt (15.2 KB)
  • 3. How DataFrames Work.srt (9.0 KB)
  • 2. DataFrames Basics Exercises.srt (8.9 KB)
  • 6. DataFrames Columns & Expressions.mp4 (205.7 MB)
  • 1. DataFrames Basics.mp4 (198.3 MB)
  • 6. DataFrames Columns & Expressions.srt (192.9 MB)
  • 9. DataFrame Joins.srt (180.8 MB)
  • 9. DataFrame Joins.mp4 (180.8 MB)
  • 7. Columns & Expressions Exercise.mp4 (172.4 MB)
  • 10. DataFrame Joins Exercise.mp4 (164.6 MB)
  • 4. Data Sources.mp4 (105.8 MB)
  • 2. DataFrames Basics Exercises.mp4 (68.6 MB)
  • 3. How DataFrames Work.mp4 (35.6 MB)
3. Spark Types and Datasets
  • 1. Working with Common Spark Data Types.srt (30.8 KB)
  • 2. Working with Complex Spark Data Types.srt (22.1 KB)
  • 3. Managing Nulls in Data.srt (20.1 KB)
  • 5. Datasets, Part 2 + Exercise.srt (18.0 KB)
  • 1. Working with Common Spark Data Types.mp4 (216.0 MB)
  • 4. Type-Safe Data Processing Datasets.mp4 (207.1 MB)
  • 2. Working with Complex Spark Data Types.mp4 (194.9 MB)
  • 5. Datasets, Part 2 + Exercise.mp4 (151.6 MB)
  • 3. Managing Nulls in Data.mp4 (120.6 MB)
  • 4. Type-Safe Data Processing Datasets.srt (5.1 MB)
1. Welcome
  • 3. Scala Recap.srt (29.2 KB)
  • 1. Welcome!.srt (16.0 KB)
  • 4. Spark First Principles.srt (13.3 KB)
  • 2. How to Make the Best out of This Course.srt (3.8 KB)
  • 3. Scala Recap.mp4 (126.3 MB)
  • 1. Welcome!.mp4 (86.2 MB)
  • 4. Spark First Principles.mp4 (46.4 MB)
  • 2. How to Make the Best out of This Course.mp4 (13.4 MB)
4. Spark SQL
  • 3. Spark SQL Exercises.srt (23.5 KB)
  • 2. Spark SQL.srt (19.9 KB)
  • 1. Spark as a Database with Spark SQL Shell.srt (15.7 KB)
  • 3. Spark SQL Exercises.mp4 (183.8 MB)
  • 2. Spark SQL.mp4 (176.8 MB)
  • 1. Spark as a Database with Spark SQL Shell.mp4 (79.2 MB)
5. Low-Level Spark
  • 1. RDDs.srt (20.4 KB)
  • 2. RDDs, Part 2 + Exercise.mp4 (216.4 MB)
  • 1. RDDs.mp4 (118.3 MB)
  • 2. RDDs, Part 2 + Exercise.srt (46.6 MB)
6. Epilogue
  • 1. You Rock!.srt (0.6 KB)
  • 1. You Rock!.mp4 (3.9 MB)
  • TutsNode.com.txt (0.1 KB)
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  • [TGx]Downloaded from torrentgalaxy.to .txt (0.6 KB)

Description


Description

UPDATED FOR SPARK 3.0

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!
Who this course is for:

   Future data scientists
   Programmers getting into the field of Big Data
   Engineers wanting to learn Spark in Scala, its native language

Requirements

   Scala fundamentals, at the level of the Rock the JVM beginners course
   Scala advanced – implicits

Last Updated 3/2021



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3.9 GB
seeders:14
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Udemy - Spark 3.0 & Big Data Essentials with Scala


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