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Programming MapReduce with Scalding

You're reading from   Programming MapReduce with Scalding A practical guide to designing, testing, and implementing complex MapReduce applications in Scala

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Product type Paperback
Published in Jun 2014
Publisher
ISBN-13 9781783287017
Length 148 pages
Edition 1st Edition
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Author (1):
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Antonios Chalkiopoulos Antonios Chalkiopoulos
Author Profile Icon Antonios Chalkiopoulos
Antonios Chalkiopoulos
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Table of Contents (11) Chapters Close

Preface 1. Introduction to MapReduce 2. Get Ready for Scalding FREE CHAPTER 3. Scalding by Example 4. Intermediate Examples 5. Scalding Design Patterns 6. Testing and TDD 7. Running Scalding in Production 8. Using External Data Stores 9. Matrix Calculations and Machine Learning Index

Exploring ad targeting

As part of our second example, we will explore the same logfiles with another job for the purpose of generating personalized ads. Let's assume that the company we are working for provides news articles with associated videos to users. For the purpose of the example, we will assume that four categories of news are presented: sports, technology, culture, and travel.

Category

Subcategories

Sports

Football

Rugby

Tennis

F1

Cycling

Tech

Games

Mobile

Gadget

Apps

Internet

Culture

Books

Film

Music

Art

Theatre

Travel

Hotels

Skiing

Family

Budget

Breaks

Analyzing and understanding the data deeply, requires lots of exploration. Fortunately, a Data Scientist validates and calculates some assumptions that result in the following conclusions:

  • Our users spend time reading articles and spend more than 20 seconds if they are slightly interested and more than 60 seconds if they are really interested.
  • Users who also view the video accompanying each article...
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