Book Image

Frank Kane's Taming Big Data with Apache Spark and Python

By : Frank Kane
Book Image

Frank Kane's Taming Big Data with Apache Spark and Python

By: Frank Kane

Overview of this book

Frank Kane’s Taming Big Data with Apache Spark and Python is your companion to learning Apache Spark in a hands-on manner. Frank will start you off by teaching you how to set up Spark on a single system or on a cluster, and you’ll soon move on to analyzing large data sets using Spark RDD, and developing and running effective Spark jobs quickly using Python. Apache Spark has emerged as the next big thing in the Big Data domain – quickly rising from an ascending technology to an established superstar in just a matter of years. Spark allows you to quickly extract actionable insights from large amounts of data, on a real-time basis, making it an essential tool in many modern businesses. Frank has packed this book with over 15 interactive, fun-filled examples relevant to the real world, and he will empower you to understand the Spark ecosystem and implement production-grade real-time Spark projects with ease.
Table of Contents (13 chapters)
Title Page
Credits
About the Author
www.PacktPub.com
Customer Feedback
Preface
7
Where to Go From Here? – Learning More About Spark and Data Science

Running the similar-movies script using Spark's cluster manager


Leading up to this point has been a lot of work, but we now have a Spark program that should give us similar movies to each other. We can figure out what movies are similar to each other, just based on similarities between user ratings. Let's turn this movie similarities problem into some real code, run it, and look at the results. Go to the download package for this book, you will find a movie-similarities script. Download that to your SparkCourse folder and open it up. We're going to keep on using the MovieLens 100,000 rating dataset for this example, so there's no new data to download, just the script. This is the most complicated thing we're going to do in this course, so let's just get through the script and walk through what it's doing. We described it at a high level in the previous section, but let's go through it again.

Examining the script

You can see we're importing the usual stuff at the top of the script. We do need...