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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 (13) Chapters

Title Page

Credits

About the Author

www.PacktPub.com

Customer Feedback

Preface

1. Getting Started with Spark FREE CHAPTER

2. Spark Basics and Spark Examples

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 script - discover who the most popular superhero is

Let's dive into the code for finding the most popular superhero in the Marvel Universe and get our answer. Who will it be? We'll find out soon. Go to the download package for this bookÂ and you're going to download three things: the Marvel-graph.txt data file, which contains our social network of superheroes, the Marvel-names.txt file, which maps superhero IDs to human-readable names, and finally, the most-popular-superhero script. Download all that into your SparkCourse folder and then open up most-popular-superhero.py in your Python environment:

Alright, let's see what's going on here. We have the usual stuff at the top so let's get down to the meat of it

Mapping input data to (hero ID, number of co-occurrences) per line

The first thing we do, if you look at line 14, is load up our names.txt file into an RDD called names using sc.textFile:

names = sc.textFile("file:///SparkCourse/marvel-names.txt")

We're going to do this name...

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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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