If you are a developer building an app today then you know how important a good search experience is. Apache Solr, built on Apache Lucene, is a wildly popular open source enterprise search server that easily delivers powerful search and faceted navigation features that are elusive with databases. Solr supports complex search criteria, faceting, result highlighting, query-completion, query spell-check, relevancy tuning, and more. Apache Solr 3 Enterprise Search Server is a comprehensive reference guide for every feature Solr has to offer. It serves the reader right from initiation to development to deployment. It also comes with complete running examples to demonstrate its use and show how to integrate Solr with other languages and frameworks. Through using a large set of metadata about artists, releases, and tracks courtesy of the MusicBrainz.org project, you will have a testing ground for Solr, and will learn how to import this data in various ways. You will then learn how to search this data in different ways, including Solr's rich query syntax and "boosting" match scores based on record data. Finally, we'll cover various deployment considerations to include indexing strategies and performance-oriented configuration that will enable you to scale Solr to meet the needs of a high-volume site. What you will learn from this book Design a schema to include text indexing details like tokenization, stemming, and synonyms Import data using various formats like CSV, XML, and from databases, and extract text from common document formats Search using Solr's rich query syntax, perform geospatial searches, and influence relevancy order Enhance search results with faceting, query spell-checking, auto-completing queries, highlighted search results, and more Integrate a host of technologies with Solr from the server side to client-side JavaScript, to frameworks like Drupal Scale Solr by learning how to tune it and how to use replication and sharding
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