Elasticsearch is a distributed search server similar to Apache Solr with a focus on large datasets, schema-less set-up, and high availability. Utilizing the Apache Lucene library (also used in Apache Solr), Elasticsearch enables powerful full-text search as well as autocomplete, "morelikethis" search and multilingual functionality, as well as an extensive search query DSL.
Elasticsearch's schema-free architecture provides developers built-in flexibility as well as ease of setup. This architecture allows Elasticsearch to index and search unstructured content, making it perfectly suited for both small projects and large big data warehouses - even with petabytes of unstructured data.
This book starts with the creation of a Google-like web search service, enabling you to generate your own search results. You will then learn how an e-commerce website can be built using Elasticsearch that will help users search and narrow down the set of products they are interested in. You will explore the most important part of a search - relevancy - based on various parameters such as relevance, document collection relevance, user usage pattern, geographic nearness, and document relevance, to select the top results.
Next, you will discover how Elasticsearch manages relational content for even complex, real-world data. You will then learn the capabilities of Elasticsearch as a strong analytic search platform, which coupled with some visualization techniques, can produce real-time data visualization. You will also discover how to improve search quality and widen the scope of matches using various analyzer techniques. Finally, the book will cover the various geo capabilities of Elasticsearch to make your searches similar to real-world scenarios.