Whether you need full-text search or real-time analytics of structured data - or both - the Elasticsearch distributed search engine is an ideal way to put your data to work. This practical guide not only shows you how to search, analyze, and explore data with Elasticsearch, but also helps you deal with the complexities of human language, geolocation, and relationships. If you're a newcomer to both search and distributed systems, you'll quickly learn how to integrate Elasticsearch into your application., More experienced users will pick up lots of advanced techniques. Throughout the book, you'll follow a problem-based approach to learn why, when, and how to use Elasticsearch features. Understand how Elasticsearch interprets data in your documents Index and query your data to take advantage of search concepts such as relevance and word proximity Handle human language through the effective use of analyzers and queries Summarize and group data to show overall trends, with aggregations and analytics Use geo-points and geo-shapes - Elasticsearch's approaches to geolocation Model your data to take advantage of Elasticsearch's horizontal scalability Learn how to configure and monitor your cluster in production
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A Distributed Real-Time Search and Analytics Engine
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 UCT in 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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