A long time ago, starting from Elasticsearch 0.90 (which was released on April 29, 2013), we got the ability to use so-called suggesters. We can define a suggester as a functionality allowing us to correct the user's spelling mistakes and build autocomplete functionality keeping performance in mind. This section is dedicated to these functionalities and will help you learn about them. We will discuss each available suggester type and show the most common properties that allow us to control them. However, keep in mind that this section is not a comprehensive guide describing each and every property. Description of all the details about suggesters are a very broad topic and is out of the scope of this book. If you want to dig into their functionality, refer to the official Elasticsearch documentation (https://www.elastic.co/guide/en/elasticsearch/reference/current/search-suggesters.html) or to the Mastering Elasticsearch Second Edition book published by Packt Publishing.
Elasticsearch Server - Third Edition
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Elasticsearch Server - Third Edition
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Overview of this book
ElasticSearch is a very fast and scalable open source search engine, designed with distribution and cloud in mind, complete with all the goodies that Apache Lucene has to offer. ElasticSearch’s schema-free architecture allows developers to index and search unstructured content, making it perfectly suited for both small projects and large big data warehouses, even those with petabytes of unstructured data.
This book will guide you through the world of the most commonly used ElasticSearch server functionalities. You’ll start off by getting an understanding of the basics of ElasticSearch and its data indexing functionality. Next, you will see the querying capabilities of ElasticSearch, followed by a through explanation of scoring and search relevance. After this, you will explore the aggregation and data analysis capabilities of ElasticSearch and will learn how cluster administration and scaling can be used to boost your application performance. You’ll find out how to use the friendly REST APIs and how to tune ElasticSearch to make the most of it. By the end of this book, you will have be able to create amazing search solutions as per your project’s specifications.
Table of Contents (18 chapters)
Elasticsearch Server Third Edition
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Preface
Free Chapter
Getting Started with Elasticsearch Cluster
Indexing Your Data
Searching Your Data
Extending Your Querying Knowledge
Extending Your Index Structure
Make Your Search Better
Aggregations for Data Analysis
Beyond Full-text Searching
Elasticsearch Cluster in Detail
Administrating Your Cluster
Scaling by Example
Index
Customer Reviews