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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

Product type Paperback

Published in Jun 2014

Publisher

ISBN-13 9781783287017

Length 148 pages

Edition 1st Edition

Languages

Scala

Tools

Hadoop

Concepts

Front End Web Development

Author (1):

Antonios Chalkiopoulos

View More author details

Table of Contents (11) Chapters

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.

The rest of the chapter is locked

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Authors (1)

Antonios Chalkiopoulos

Antonios Chalkiopoulos

Antonios Chalkiopoulos is a developer living in London and a professional working with Hadoop and Big Data technologies. He completed a number of complex MapReduce applications in Scalding into 40-plus production nodes HDFS Cluster. He is a contributor to Scalding and other open source projects, and he is interested in cloud technologies, NoSQL databases, distributed real-time computation systems, and machine learning. He was involved in a number of Big Data projects before discovering Scala and Scalding. Most of the content of this book comes from his experience and knowledge accumulated while working with a great team of engineers.

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