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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

Chapter 4. Intermediate Examples

This chapter goes through a real implementation in Scalding of non-trivial applications using the operations presented in the previous chapter. We will go through the data analysis, design, implementation, and optimization of data-transformation jobs for the following:

  • Logfile analysis
  • Ad targeting

Analyzing logfiles that have been stored for some time is a usual starting application of a new Hadoop team in an organization. The type of value to extract from the logfiles depends on the use case. As an example, we will use a case where we will need to think a lot about how to manage the data.

Another example of Ad targeting will make us look at how to structure and store the data to allow us to run daily jobs. It will involve input from data scientists and deep analysis of customer behavior to recommend personalized advertisements.

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