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Mastering Spark for Data Science

You're reading from   Mastering Spark for Data Science Lightning fast and scalable data science solutions

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Product type Paperback
Published in Mar 2017
Publisher Packt
ISBN-13 9781785882142
Length 560 pages
Edition 1st Edition
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Authors (5):
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 Bifet Bifet
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Bifet
 Morgan Morgan
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Morgan
 Amend Amend
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 Hallett Hallett
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Hallett
 George George
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George
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Table of Contents (22) Chapters Close

Mastering Spark for Data Science
Credits
Foreword
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. The Big Data Science Ecosystem FREE CHAPTER 2. Data Acquisition 3. Input Formats and Schema 4. Exploratory Data Analysis 5. Spark for Geographic Analysis 6. Scraping Link-Based External Data 7. Building Communities 8. Building a Recommendation System 9. News Dictionary and Real-Time Tagging System 10. Story De-duplication and Mutation 11. Anomaly Detection on Sentiment Analysis 12. TrendCalculus 13. Secure Data 14. Scalable Algorithms

Data security


The final piece to our data architecture is security, and in this chapter we will discover that data security is always important, and the reasons for this. Given the huge increase in the volume and variety of data in recent times, caused by many factors, but in no small part due to the popularity of the Internet and related technologies, there is a growing need to provide fully scalable and secure solutions. We are going to explore those solutions along with the confidentiality, privacy, and legal concerns associated with the storing, processing, and handling of data; we will relate these to the tools and techniques introduced in previous chapters.

We will continue on by explaining the technical issues involved in securing data at scale and introduce ideas and techniques that tackle these concerns using a variety of access, classification, and obfuscation strategies. As in previous chapters, ideas are demonstrated with examples using the Hadoop ecosystem, and public cloud infrastructure...

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