Apache Spark with Scala - Hands On with Big Data!

4.5 (11692)
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Обучение платное
Language
Английский
Duration
9 часов курса
Курс от Udemy
Чему вы научились?
Frame big data analysis problems as Apache Spark scripts
Develop distributed code using the Scala programming language
Optimize Spark jobs through partitioning, caching, and other techniques
Build, deploy, and run Spark scripts on Hadoop clusters
Process continual streams of data with Spark Streaming
Transform structured data using SparkSQL, DataSets, and DataFrames
Traverse and analyze graph structures using GraphX
Analyze massive data set with Machine Learning on Spark
О курсе

New! Completely updated and re-recorded for Spark 3, IntelliJ, Structured Streaming, and a stronger focus on the DataSet API.

“Big data" analysis is a hot and highly valuable skill – and this course will teach you the hottest technology in big data: Apache Spark. Employers including AmazonEBayNASA JPL, and Yahoo all use Spark to quickly extract meaning from massive data sets across a fault-tolerant Hadoop cluster. You'll learn those same techniques, using your own Windows system right at home. It's easier than you might think, and you'll be learning from an ex-engineer and senior manager from Amazon and IMDb.

Spark works best when using the Scala programming language, and this course includes a crash-course in Scala to get you up to speed quickly. For those more familiar with Python however, a Python version of this class is also available: "Taming Big Data with Apache Spark and Python - Hands On".

Learn and master the art of framing data analysis problems as Spark problems through over 20 hands-on examples, and then scale them up to run on cloud computing services in this course.

  • Learn the concepts of Spark's Resilient Distributed Datasets, DataFrames, and Datasets.
  • Get a crash course in the Scala programming language
  • Develop and run Spark jobs quickly using Scala, IntelliJ, and SBT
  • Translate complex analysis problems into iterative or multi-stage Spark scripts
  • Scale up to larger data sets using Amazon's Elastic MapReduce service
  • Understand how Hadoop YARN distributes Spark across computing clusters
  • Practice using other Spark technologies, like Spark SQL, DataFrames, DataSets, Spark Streaming, Machine Learning, and GraphX

By the end of this course, you'll be running code that analyzes gigabytes worth of information – in the cloud – in a matter of minutes. 

We'll have some fun along the way. You'll get warmed up with some simple examples of using Spark to analyze movie ratings data and text in a book. Once you've got the basics under your belt, we'll move to some more complex and interesting tasks. We'll use a million movie ratings to find movies that are similar to each other, and you might even discover some new movies you might like in the process! We'll analyze a social graph of superheroes, and learn who the most “popular" superhero is – and develop a system to find “degrees of separation" between superheroes. Are all Marvel superheroes within a few degrees of being connected to SpiderMan? You'll find the answer.

This course is very hands-on; you'll spend most of your time following along with the instructor as we write, analyze, and run real code together – both on your own system, and in the cloud using Amazon's Elastic MapReduce service. over 8 hours of video content is included, with over 20 real examples of increasing complexity you can build, run and study yourself. Move through them at your own pace, on your own schedule. The course wraps up with an overview of other Spark-based technologies, including Spark SQL, Spark Streaming, and GraphX.

Enroll now, and enjoy the course!

"I studied Spark for the first time using Frank's course "Apache Spark 2 with Scala - Hands On with Big Data!". It was a great starting point for me,  gaining knowledge in Scala and most importantly practical examples of Spark applications. It gave me an understanding of all the relevant Spark core concepts,  RDDs, Dataframes & Datasets, Spark Streaming, AWS EMR. Within a few months of completion, I used the knowledge gained from the course to propose in my current company to  work primarily on Spark applications. Since then I have continued to work with Spark. I would highly recommend any of Franks courses as he simplifies concepts well and his teaching manner is easy to follow and continue with!  " - Joey Faherty

Программа
Getting Started
Install a complete Spark / Scala development environment, and run a simple Scala program in Spark.
Tip: Apply for a Twitter Developer Account now!
Udemy 101: Getting the Most From This Course
Warning about Java 11 and Spark 2.4!
Be sure to install a JDK for Java 8 for this course, NOT Java 9, 10, or 11 - and install Spark 2.3, not 2.4.0.
Introduction, and Getting Set Up
A brief introduction to the course, and then we'll get your development environment for Spark and Scala all set up on your desktop. A quick test application will confirm Spark is working on your system! Remember - be sure to install Spark 2.2 andJava 8 for this course.
[Activity] Create a Histogram of Real Movie Ratings with Spark!
Let's dive right in! We'll download a data set of 100,000 real movie ratings from real people, and run a Spark script that generates histogram data of the distribution of movie ratings. Some final setup of your Scala development environment and downloading the course materials is also part of this lecture, so be sure not to skip this one.
Scala Crash Course [Optional]
Understand the basics of Scala and code simple Scala programs.
[Activity] Scala Basics, Part 1
We'll go over the basic syntax and structure of Scala code with lots of examples. It's backwards from most other languages, but you quickly get used to it. Part 1 of 2.
[Exercise] Scala Basics, Part 2
We'll go over the basic syntax and structure of Scala code with lots of examples. It's backwards from most other languages, but you quickly get used to it. Part 2 of 2, with some hands-on practice at the end.
[Exercise] Flow Control in Scala
You'll see how flow control works in Scala (if/then statements, loops, etc.), and practice what you've learned at the end.
[Exercise] Functions in Scala
Scala is a functional programming language, and so functions are central to the language. We'll go over the many ways functions can be declared and used in Scala, and practice what you've learned.
[Exercise] Data Structures in Scala
We'll cover the common data structures in Scala such as Map and List, and put them into practice.
Требования
  • Some prior programming or scripting experience is required. A crash course in Scala is included, but you need to know the fundamentals of programming in order to pick it up.
  • You will need a desktop PC and an Internet connection. The course is created with Windows in mind, but users comfortable with MacOS or Linux can use the same tools.
  • The software needed for this course is freely available, and I'll walk you through downloading and installing it.
Лекторы
Sundog Education by Frank Kane
Sundog Education by Frank Kane
Founder, Sundog Education. Machine Learning Pro
Frank Kane
Frank Kane
Founder, Sundog Education
Платформа
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Курсы Udemy подойдут для профессионального развития. Платформа устроена таким образом, что эксперты сами запускают курсы. Все материалы передаются в пожизненный доступ. На этой платформе можно найти курс, без преувеличений, на любую тему – начиная от тьюториала по какой-то камере и заканчивая теоретическим курсом по управлению финансовыми рисками. Язык и формат обучения устанавливается преподавателем, поэтому стоит внимательно изучить информацию о курсе перед покупкой.
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