Book Image

Mastering Elasticsearch 5.x - Third Edition

By : Bharvi Dixit
Book Image

Mastering Elasticsearch 5.x - Third Edition

By: Bharvi Dixit

Overview of this book

Elasticsearch is a modern, fast, distributed, scalable, fault tolerant, and open source search and analytics engine. Elasticsearch leverages the capabilities of Apache Lucene, and provides a new level of control over how you can index and search even huge sets of data. This book will give you a brief recap of the basics and also introduce you to the new features of Elasticsearch 5. We will guide you through the intermediate and advanced functionalities of Elasticsearch, such as querying, indexing, searching, and modifying data. We’ll also explore advanced concepts, including aggregation, index control, sharding, replication, and clustering. We’ll show you the modules of monitoring and administration available in Elasticsearch, and will also cover backup and recovery. You will get an understanding of how you can scale your Elasticsearch cluster to contextualize it and improve its performance. We’ll also show you how you can create your own analysis plugin in Elasticsearch. By the end of the book, you will have all the knowledge necessary to master Elasticsearch and put it to efficient use.
Table of Contents (20 chapters)
Mastering Elasticsearch 5.x - Third Edition
About the Author
About the Reviewer
Customer Feedback


Before we continue with querying and analyzing the responses, we would like to write a few words about the available suggester types—the functionality responsible for finding suggestions when using the Elasticsearch suggest API. Elasticsearch allows us to use four suggesters currently: the term one, the phrase one, the completion one, and the context one. The first two allow us to correct spelling mistakes, while the third and fourth ones allow us to develop a very fast autocomplete functionality. However, for now, let's not focus on any particular suggester type, but let's look at the query possibilities and the responses returned by Elasticsearch. We will try to show you the general principles, and then we will get into more detail about each of the available suggesters.

Using a suggester under the _search endpoint

Before Elasticsearch 5.0, there was a possibility to get suggestions for a given text by using a dedicated _suggest REST endpoint. But in Elasticsearch 5.0, this dedicated...