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

Superhero degrees of separation - introducing the breadth-first search algorithm


You might have heard how everyone is connected through six degrees of separation. Somebody you know knows somebody else who knows somebody else and so on; eventually, you can be connected to pretty much everyone on the planet. Or maybe you've heard about how Kevin Bacon is within a few degrees of separation of pretty much everybody in Hollywood. Well, I used to work at imdb.com, and I can tell you that is true, Kevin Bacon is pretty well connected, but a lot of other actors are too. Kevin Bacon is actually not the most connected actor, but I digress! We want to bring this concept of degrees of separation to our superhero dataset, where we have this virtual social network of superheroes.

Let's figure out the degrees of separation between any two superheroes in that dataset. Is the Hulk connected to Spider-Man closely? How do you find how many connections there are between any two given superheroes that we have...