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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 (8) Chapters Close

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

Creating similar movies from one million ratings - part 1


Let's modify our movie-similarities script to actually work on the 1 million ratings dataset and make it so it can run in the cloud on Amazon Elastic MapReduce, or any Spark cluster for that matter. So, if you haven't already, go grab the movie-similarities-1m Python script from the download package for this book, and save it wherever you want to. It's actually not that important where you save this one because we're not going to run it on your desktop anyway, you just need to look at it and know where it is. Open it up, just so we can take a peek, and I'll walk you through the stuff that we actually changed:

Changes to the script

Now, first of all, we made some changes so that it uses the 1 million ratings dataset from Grouplens instead of the 100,000 ratings dataset. If you want to grab that, go over to grouplens.org and click on datasets:

You'll find it in the MovieLens 1M Dataset:

This data is a little bit more current, it's from...

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