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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

Summary

This concludes the part of the course about Spark core, covering the things you can do with Spark itself. We did pretty much everything there is to do, and we actually ran a million ratings, and analyzed on a real cluster in the cloud using Spark. So congratulations, if you've got this far! You are now pretty knowledgeable about Spark. In the next chapter, we'll talk about some of the technologies built on top of Spark that are still part of this greater Spark package.

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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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