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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

Configuring using a property file


To read configuration data from a property file, we can use the configuration library for JVM languages from typesafe. This is mostly a Scala feature, but an interesting example is running Scalding applications in two different clusters.

While during developing and testing, we execute our Scalding application in a development cluster, when the jobs are production ready, they are executed in a powerful production Hadoop cluster.

In this case, each cluster will have different configuration requirements. To solve this issue, first define two property files as shown:

  dev-cluster.properties
  production-cluster.properties

Each file contains environment and job configuration information. For example, the file dev-cluster.properties can contain the following:

  mysql=dev.mysql.company.com
  zookeeper=dev.zookeeper.company.com:2181
  reducers=30

The best way to implement this capability (keeping in mind the single responsibility principle) is in a different class...

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