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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

Search platforms


The Apache Lucene library provides Java-based indexing and search technology as well as spellchecking, hit highlighting, advanced analysis, and tokenization capabilities. There are two popular open source projects that use this library and provide a distributed platform with replication and caching capabilities.

Solr has been an Apache open source project since 2006, and thus, it has been used by many enterprises and has grown and improved as a project. ElasticSearch was released a few years later, and it was designed since the beginning to be distributed and easy-to-scale out to handle massive amounts of data.

As distributed systems, they both fit nicely in the Hadoop environment. Nodes that participate in the cluster can run both the Hadoop applications—an HBase database and a search platform.

As high memory nodes are usually in place, we can allocate enough memory to each system. Then, depending on the job running, we can utilize the processing and caching capabilities of...

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