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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

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Product type Paperback
Published in Jun 2017
Publisher Packt
ISBN-13 9781787287945
Length 296 pages
Edition 1st Edition
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Concepts
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Author (1):
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Frank Kane Frank Kane
Author Profile Icon Frank Kane
Frank Kane
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Table of Contents (13) Chapters Close

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

Check your sorted implementation and results against mine


Let's take a look at my implementation of sorting the results for the total amount spent by customer and compare it with yours. If you got to this point and you haven't actually tried this yourself or you got stuck, let me give you one more hint before I show you my solution. If you look at the word-count-better-sorted script that we used in the previous example for doing word frequency counts sorted by word frequency, you'll see that we did something very similar in there. If you got stuck, have a look at that script and give it another try first before you peek at the answer here.

If you've given it a try, go ahead and download the total-spent-by-customer-sorted script from the download package for this book and compare your solution to mine. There's more than one way to do these things, so just because I did it one way it doesn't mean you can't do it another way. As long as it works, that's what matters:

You can see all I really...

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