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 average friends by age example


Okay, let's make it real, let's actually get some real code and some real data and analyze the average number of friends by age in our fabricated dataset here, and see what we come up with.

At this point, you should go to the download package for this book, if you haven't already, and download two things: one is the friends-by-age Python script, and the other is the fakefriends.csv file, which is my randomly generated data that's completely fictitious, but useful for illustration. So go take care of that now. When you're done, move it into your C:\SparkCourse folder or wherever you're installing stuff for this course. At this point in the course, your SparkCourse folder should look like this:

At this moment, we need friends-by-age.py and fakefriends.csv, so let's double-click on the friends-by-age.py script, and Enthought Canopy or your Python environment of choice should come up. Here we have it:

Examining the script

So let's just review again what...