Apache Solr 3 Enterprise Search Server

Overview

• This book is an update of our previous edition, written to Solr 1.4

Apache Solr 3.1 Enterprise Search Server is for developers who want to learn how to use Solr in their applications. Only basic programming skills are needed. The book is written as a reference guide and includes fully working examples based on a real-world public data set.

Through using a large set of metadata about artists, releases, and tracks courtesy of the ...

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Apache Solr 3 Enterprise Search Server

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Overview

• This book is an update of our previous edition, written to Solr 1.4

Apache Solr 3.1 Enterprise Search Server is for developers who want to learn how to use Solr in their applications. Only basic programming skills are needed. The book is written as a reference guide and includes fully working examples based on a real-world public data set.

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.

Apache Solr 3.1 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.

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Product Details

  • ISBN-13: 9781849516068
  • Publisher: Packt Publishing
  • Publication date: 10/22/2011
  • Pages: 418
  • Product dimensions: 7.50 (w) x 9.25 (h) x 0.85 (d)

Meet the Author

David Smiley: Born to code, David Smiley is a senior software engineer, book author, conference speaker, and instructor. He has 12 years of experience in the defense industry at MITRE, specializing in Java and Web technologies. David is the principal author of "Solr 1.4 Enterprise Search Server", the first book on Solr, published by PACKT in 2009. He also developed and taught a two-day course on Solr for MITRE. David plays a lead technical role in a large-scale Solr project in which he has implemented geospatial search based on geohash prefixes, wildcard ngram query parsing, searching multiple multi-valued fields at coordinated positions, part-of-speech search using Lucene payloads, and other things. David consults as a Solr expert on numerous projects for MITRE and its government sponsors. He has contributed code to Lucene and Solr and is active in the open-source community. Prior to his Solr work, David first used Lucene back in 2000, as well as Hibernate-Search and Compass since then. He also used the competing Endeca commercial product, too, but hopes to never use it again.

Eric Pugh: Fascinated by the 'craft' of software development, Eric Pugh has been heavily involved in the open source world as a developer, committer, and user for the past five years. He is an emeritus member of the Apache Software Foundation and lately has been mulling over how we solve the problem of finding answers in datasets when we don't know the questions ahead of time to ask.

In biotech, financial services, and defense IT, he has helped European and American companies develop coherent strategies for embracing open source search software. As a speaker, he has advocated the advantages of Agile practices with a focus on testing in search engine implementation.

Eric became involved with Solr when he submitted the patch SOLR-284 for Parsing Rich Document types such as PDF and MS Office formats that became the single most popular patch as measured by votes! The patch was subsequently cleaned up and enhanced by three other individuals, demonstrating the power of the open source model to build great code collaboratively. SOLR-284 was eventually refactored into Solr Cell as part of Solr version 1.4.

He blogs at http://www.opensourceconnections.com/

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