Contents

foreword
preface
preface to the first edition
acknowledgments
about this book
about the authors
JUnit primer

Part 1 Core Lucene

Chapter 1 Meet Lucene: Dealing with information explosion; What is Lucene?; Lucene and the components of a search application; Lucene in action: a sample application; Understanding the core indexing classes; Understanding the core searching classes; Summary
Chapter 2 Building a search index: How Lucene models content; Understanding the indexing process; Basic index operations; Field options; Boosting documents and fields; Indexing numbers, dates, and times; Field truncation; Near-real-time search; Optimizing an index; Other directory implementations; Concurrency, thread safety, and locking issues; Debugging indexing; Advanced indexing concepts; Summary
Chapter 3 Adding search to your application: Implementing a simple search feature; Using IndexSearcher; Understanding Lucene scoring; Lucene’s diverse queries; Parsing query expressions: QueryParser; Summary
Chapter 4 Lucene’s analysis process: Using analyzers; What’s inside an analyzer?; Using the built-in analyzers; Sounds-like querying; Synonyms, aliases, and words that mean the same; Stemming analysis; Field variations; Language analysis issues; Nutch analysis; Summary
Chapter 5 Advanced search techniques: Lucene’s field cache; Sorting search results; Using MultiPhraseQuery; Querying on multiple fields at once; Span queries; Filtering a search; Custom scoring using function queries; Searching across multiple Lucene indexes; Leveraging term vectors; Loading fields with FieldSelector; Stopping a slow search; Summary
Chapter 6 Extending search: Using a custom sort method; Developing a custom Collector; Extending QueryParser; Custom filters; Payloads; Summary

Part 2 Applied Lucene

Chapter 7 Extracting text with Tika: What is Tika?; Tika’s logical design and API; Installing Tika; Tika’s built-in text extraction tool; Extracting text programmatically; Tika’s limitations; Indexing custom XML; Alternatives; Summary
Chapter 8 Essential Lucene extensions: Luke, the Lucene Index Toolbox; Analyzers, tokenizers, and TokenFilters; Highlighting query terms; FastVectorHighlighter; Spell checking; Fun and interesting Query extensions; Building contrib modules; Summary
Chapter 9 Further Lucene extensions: Chaining filters; Storing an index in Berkeley DB; Synonyms from WordNet; Fast memory-based indices; XML QueryParser: Beyond “one box” search interfaces; Surround query language; Spatial Lucene; Searching multiple indexes remotely; Flexible QueryParser; Summary
Chapter 10 Using Lucene from other programming languages: Ports primer; CLucene (C++); Lucene.Net (C# and other .NET languages); KinoSearch and Lucy (Perl); Ferret (Ruby); PHP; PyLucene (Python); Solr (many programming languages); Summary
Chapter 11 Lucene administration and performance tuning: Performance tuning; Threads and concurrency; Managing resource consumption; Hot backups of the index; Common errors; Summary

Part 3 Case studies

Chapter 12 Case study 1: Krugle
Krugle: Searching source code: Introducing Krugle; Appliance architecture; Search performance; Parsing source code; Substring searching; Query vs. search; Future improvements; Summary
Chapter 13 Case study 2: SIREn
Searching semistructured documents with SIREn: Introducing SIREn; SIREn’s benefits; Indexing entities with SIREn; Searching entities with SIREn; Integrating SIREn in Solr; Benchmark; Summary
Chapter 14 Case study 3: LinkedIn
Adding facets and real-time search with Bobo Browse and Zoie: Faceted search with Bobo Browse; Real-time search with Zoie; Summary