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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

Chapter 3. Scalding by Example

This chapter presents how to read and write local and Hadoop Distributed File System (HDFS) files with Scalding. It introduces the complete Scalding core capabilities through the Fields API and serves as a reference to look up how the Scalding commands can be used. In this chapter, we will cover:

Map-like operations
Join operations
Pipe operations
Grouping and reducing operations
Composite operations

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.

See other products by Antonios Chalkiopoulos

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