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.
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.
Trey Grainger is the Chief Algorithms Officer at Lucidworks, the AI-powered search company that powers hundreds of the world’s leading organizations. Trey co-authored Solr in Action and has over 12 years experience building semantic search engines, recommendation engines, real-time analytics systems, and leading related engineering and data science teams.
Timothy Potter is an architect on the Big Data team at Dachis Group, where he focuses on large-scale machine learning, text mining, and social network analysis. Tim has worked extensively with Lucene and Solr technologies and has been a speaker at Lucene Revolution. He is a contributing author to Taming Text (Manning 2012) and holds several US Patents related to J2EE-based enterprise application integration. He blogs at thelabdude.blogspot.com.