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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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Amend
 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

Authentication and authorization


Authentication is related to the mechanisms used to ensure that the user is who they say they are and operates at two key levels, namely, local and remote.

Authentication can take various forms, the most common is user login, but other examples include fingerprint reading, iris scanning, and PIN number entry. User logins can be managed on a local basis, as you would on your personal computer, for example, or on a remote basis using a tool such as Lightweight Directory Access Protocol (LDAP). Managing users remotely provides roaming user profiles that are independent of any particular hardware and can be managed independently of the user. All of these methods execute at the operating system level. There are other mechanisms that sit at the application layer and provide authentication for services, such as Google OAuth.

Alternative authentication methods have their own pros and cons, a particular implementation should be understood thoroughly before declaring...

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