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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

NoSQL databases


Another common scenario is to read, insert, or update existing data in a NoSQL database. Such systems are usually used to drive real-time applications such as an Analytics platform, or store and provide traversal capabilities to a graph database.

Fortunately, a lot of taps are available, and Cascading provides a number of extensions for popular NoSQL databases such as MongoDB, Cassandra, ElaphantDB, and HBase. A brief introduction to these NoSQL systems follows:

  • MongoDB: This is a document-oriented database that uses JSON-like documents with dynamic schemas and is the most popular NoSQL database.

  • Cassandra: This is a highly distributed database capable of spanning over multiple data centers that aims to provide low latency for real-time applications. It uses a flat hierarchy across nodes architecture and is not dependent on Hadoop applications or HDFS.

  • ElephantDB: This is a distributed database specializing in exporting key-value data from Hadoop. The library elephantdb-cascading...

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