- Foreword
- Preface
- I. Getting Started
- 1. You Know, for Search…
- Installing Elasticsearch
- Running Elasticsearch
- Talking to Elasticsearch
- Document Oriented
- Finding Your Feet
- Indexing Employee Documents
- Retrieving a Document
- Search Lite
- Search with Query DSL
- More-Complicated Searches
- Full-Text Search
- Phrase Search
- Highlighting Our Searches
- Analytics
- Tutorial Conclusion
- Distributed Nature
- Next Steps
- 2. Life Inside a Cluster
- 3. Data In, Data Out
- What Is a Document?
- Document Metadata
- Indexing a Document
- Retrieving a Document
- Checking Whether a Document Exists
- Updating a Whole Document
- Creating a New Document
- Deleting a Document
- Dealing with Conflicts
- Optimistic Concurrency Control
- Partial Updates to Documents
- Retrieving Multiple Documents
- Cheaper in Bulk
- 4. Distributed Document Store
- 5. Searching—The Basic Tools
- 6. Mapping and Analysis
- 7. Full-Body Search
- 8. Sorting and Relevance
- 9. Distributed Search Execution
- 10. Index Management
- 11. Inside a Shard
- 1. You Know, for Search…
- II. Search in Depth
- 12. Structured Search
- 13. Full-Text Search
- 14. Multifield Search
- 15. Proximity Matching
- 16. Partial Matching
- 17. Controlling Relevance
- Theory Behind Relevance Scoring
- Lucene’s Practical Scoring Function
- Query-Time Boosting
- Manipulating Relevance with Query Structure
- Not Quite Not
- Ignoring TF/IDF
- function_score Query
- Boosting by Popularity
- Boosting Filtered Subsets
- Random Scoring
- The Closer, The Better
- Understanding the price Clause
- Scoring with Scripts
- Pluggable Similarity Algorithms
- Changing Similarities
- Relevance Tuning Is the Last 10%
- III. Dealing with Human Language
- 18. Getting Started with Languages
- 19. Identifying Words
- 20. Normalizing Tokens
- 21. Reducing Words to Their Root Form
- 22. Stopwords: Performance Versus Precision
- 23. Synonyms
- 24. Typoes and Mispelings
- IV. Aggregations
- 25. High-Level Concepts
- 26. Aggregation Test-Drive
- 27. Building Bar Charts
- 28. Looking at Time
- 29. Scoping Aggregations
- 30. Filtering Queries and Aggregations
- 31. Sorting Multivalue Buckets
- 32. Approximate Aggregations
- 33. Significant Terms
- 34. Controlling Memory Use and Latency
- 35. Closing Thoughts
- V. Geolocation
- VI. Modeling Your Data
- 40. Handling Relationships
- 41. Nested Objects
- 42. Parent-Child Relationship
- 43. Designing for Scale
- VII. Administration, Monitoring, and Deployment
- 44. Monitoring
- 45. Production Deployment
- 46. Post-Deployment
- Index
About the Authors
Clinton Gormley was the first user of Elasticsearch and wrote the Perl API back in 2010. When Elasticsearch formed a company in 2012, he joined as a developer and the maintainer of the Perl modules. Now Clinton spends a lot of his time designing the user interfaces and speaking and writing about Elasticsearch. He studied medicine at the University of Cape Town and lives in Barcelona.
Zachary Tong has been working with Elasticsearch since 2011. During that time, he has written a number of tutorials to help beginners start using Elasticsearch. Zach is now a developer at Elasticsearch and maintains the PHP client, gives trainings, and helps customers manage clusters in production. He studied biology at Rensselaer Polytechnic Institute and now lives in South Carolina.
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