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

You're reading from Frank Kane's Taming Big Data with Apache Spark and Python Real-world examples to help you analyze large datasets with Apache Spark

Product type Paperback

Published in Jun 2017

Publisher Packt

ISBN-13 9781787287945

Length 296 pages

Edition 1st Edition

Languages

Python

Tools

Apache Spark

Concepts

Big Data

Author (1):

Frank Kane

View More author details

Table of Contents (8) Chapters

Preface

1. Getting Started with Spark

2. Spark Basics and Spark Examples FREE CHAPTER

3. Advanced Examples of Spark Programs

4. Running Spark on a Cluster

5. SparkSQL, DataFrames, and DataSets

6. Other Spark Technologies and Libraries

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...

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

Published in: Jun 2017

Publisher: Packt

ISBN-13: 9781787287945

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Authors (1)

Frank Kane

Frank Kane

Frank Kane has spent nine years at Amazon and IMDb, developing and managing the technology that automatically delivers product and movie recommendations to hundreds of millions of customers all the time. He holds 17 issued patents in the fields of distributed computing, data mining, and machine learning. In 2012, Frank left to start his own successful company, Sundog Software, which focuses on virtual reality environment technology and teaches others about big data analysis.

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