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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

Summary


In this chapter, executing and scheduling jobs were presented. As our data processing workflows can depend on a number of applications, we showed how to chain together and coordinate the execution of a number of tasks. Then, we proceeded with configuring our jobs using both property files and Hadoop parameters.

Monitoring and optimizing our job execution was also presented. Finally, two more techniques we presented about using slim jars were to optimize the deployment process and how to throttle job execution.

In the next chapter, we will see how to use external data sources to read data from and store data to.

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