Solr in Action

Type
Book
Authors
Grainger ( Trey )
Potter ( Timothy )
 
ISBN 10
1617291021 
ISBN 13
9781617291029 
Category
 
Publication Year
2014 
Publisher
Manning Publications, United States 
Pages
664 
Subject
A comprehensive guide to implementing scalable search using Apache Solr 
Description
Solr in Action is a comprehensive guide to implementing scalable search using Apache Solr. This clearly written book walks you through well-documented examples ranging from basic keyword searching to scaling a system for billions of documents and queries. It will give you a deep understanding of how to implement core Solr capabilities.

About the Book

Whether you're handling big (or small) data, managing documents, or building a website, it is important to be able to quickly search through your content and discover meaning in it. Apache Solr is your tool: a ready-to-deploy, Lucene-based, open source, full-text search engine. Solr can scale across many servers to enable real-time queries and data analytics across billions of documents.

Solr in Action teaches you to implement scalable search using Apache Solr. This easy-to-read guide balances conceptual discussions with practical examples to show you how to implement all of Solr's core capabilities. You'll master topics like text analysis, faceted search, hit highlighting, result grouping, query suggestions, multilingual search, advanced geospatial and data operations, and relevancy tuning.

This book assumes basic knowledge of Java and standard database technology. No prior knowledge of Solr or Lucene is required.

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

What's Inside

How to scale Solr for big data
Rich real-world examples
Solr as a NoSQL data store
Advanced multilingual, data, and relevancy tricks
Coverage of versions through Solr 4.7
About the Authors

Trey Grainger is a director of engineering at CareerBuilder. Timothy Potter is a senior member of the engineering team at LucidWorks. The authors work on the scalability and reliability of Solr, as well as on recommendation engine and big data analytics technologies. 
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