Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Mastering Spark for Data Science

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

Arrow left icon
Product type Paperback
Published in Mar 2017
Publisher Packt
ISBN-13 9781785882142
Length 560 pages
Edition 1st Edition
Arrow right icon
Authors (5):
Arrow left icon
David George David George
Author Profile Icon David George
David George
Matthew Hallett Matthew Hallett
Author Profile Icon Matthew Hallett
Matthew Hallett
Antoine Amend Antoine Amend
Author Profile Icon Antoine Amend
Antoine Amend
Andrew Morgan Andrew Morgan
Author Profile Icon Andrew Morgan
Andrew Morgan
Albert Bifet Albert Bifet
Author Profile Icon Albert Bifet
Albert Bifet
+1 more Show less
Arrow right icon
View More author details
Toc

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

GIS lookup


In the previous section, we were covering an interesting use case, how to extract location entities from unstructured data. In this section, we will make our enrichment process even smarter by trying to retrieve the actual geographical coordinate information (such as latitude and longitude) based on the locations of entities we were able to identify. Given an input string London, can we detect the city of London - UK together with its relative latitude and longitude? We will be discussing how to build an efficient geo lookup system that does not rely on any external API and which can process location data of any scale by leveraging the Spark framework and the Reduce-Side-Join pattern. When building this lookup service, we will have to bear in mind many places around the world might be sharing the same name (there are around 50 different places called Manchester in the US alone), and that an input record may not use the official name of the place it would be referring to (the official...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image