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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

We've covered a lot of ground in this chapter, and I hope it's given you an idea of the kinds of things that you can do with Spark and the power that it gives you. Please do continue to explore and experiment with these examples, altering things to see how they function and gaining familiarity with the workings of Spark. In the next chapter, we're going to turn our attention to the cloud and start working with really big data when we find out how to run Spark on a cluster.

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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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