- Elasticsearch - The Definitive Guide:
- Foreword
- Preface
- Getting Started
- You Know, for Search…
- Installing and 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
- Life Inside a Cluster
- 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
- Distributed Document Store
- Searching—The Basic Tools
- Mapping and Analysis
- Full-Body Search
- Sorting and Relevance
- Distributed Search Execution
- Index Management
- Inside a Shard
- You Know, for Search…
- Search in Depth
- Structured Search
- Full-Text Search
- Multifield Search
- Proximity Matching
- Partial Matching
- 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%
- Dealing with Human Language
- Aggregations
- Geolocation
- Modeling Your Data
- Administration, Monitoring, and Deployment
WARNING: This documentation covers Elasticsearch 2.x. The 2.x versions of Elasticsearch have passed their EOL dates. If you are running a 2.x version, we strongly advise you to upgrade.
This documentation is no longer maintained and may be removed. For the latest information, see the current Elasticsearch documentation.
Who Should Read This Book
editWho Should Read This Book
editThis book is for anybody who wants to put their data to work. It doesn’t matter whether you are starting a new project and have the flexibility to design the system from the ground up, or whether you need to give new life to a legacy system. Elasticsearch will help you to solve existing problems and open the way to new features that you haven’t yet considered.
This book is suitable for novices and experienced users alike. We expect you to have some programming background and, although not required, it would help to have used a relational database and SQL. We explain concepts from first principles, helping novices to gain a sure footing in the complex world of search.
The reader with a search background will also benefit from this book. The more experienced user will gain an understanding of how familiar search concepts have been implemented and how they interact in the context of Elasticsearch. Even the early chapters contain nuggets of information that will be useful to the more advanced user.
Finally, maybe you are in DevOps. While the other departments are stuffing data into Elasticsearch as fast as they can, you’re the one charged with stopping their servers from bursting into flames. Elasticsearch scales effortlessly, as long as your users play within the rules. You need to know how to set up a stable cluster before going into production, and then be able to recognize the warning signs at three in the morning in order to prevent catastrophe. The earlier chapters may be of less interest to you, but the last part of the book is essential reading—all you need to know to avoid meltdown.