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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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David George David George
Author Profile Icon David George
David George
Matthew Hallett Matthew Hallett
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Matthew Hallett
Antoine Amend Antoine Amend
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Antoine Amend
Andrew Morgan Andrew Morgan
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Andrew Morgan
Albert Bifet Albert Bifet
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Albert Bifet
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Table of Contents (15) Chapters Close

Preface 1. The Big Data Science Ecosystem 2. Data Acquisition FREE CHAPTER 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

Using the Accumulo database


We have seen a method to read our personRdd object from Elasticsearch and this forms a simple and neat solution for our storage requirements. However, when writing commercial applications, we must always be mindful of security and, at the time of writing, Elasticsearch security is still in development; so it would be useful at this stage to introduce a storage mechanism with native security. This is an important consideration we are using GDELT data that is, of course, open source by definition. In a commercial environment, it is very common for datasets to be confidential or commercially sensitive in some way, and clients will often request details of how their data will be secured long before they discuss the data science aspect itself. It is the authors experience that many a commercial opportunity is lost due to the inability of solution providers to demonstrate a robust and secure data architecture.

Accumulo (http://accumulo.apache.org) is a NoSQL database...

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