Book Image

Elasticsearch 7 Quick Start Guide

By : Anurag Srivastava, Douglas Miller
Book Image

Elasticsearch 7 Quick Start Guide

By: Anurag Srivastava, Douglas Miller

Overview of this book

Elasticsearch is one of the most popular tools for distributed search and analytics. This Elasticsearch book highlights the latest features of Elasticsearch 7 and helps you understand how you can use them to build your own search applications with ease. Starting with an introduction to the Elastic Stack, this book will help you quickly get up to speed with using Elasticsearch. You'll learn how to install, configure, manage, secure, and deploy Elasticsearch clusters, as well as how to use your deployment to develop powerful search and analytics solutions. As you progress, you'll also understand how to troubleshoot any issues that you may encounter along the way. Finally, the book will help you explore the inner workings of Elasticsearch and gain insights into queries, analyzers, mappings, and aggregations as you learn to work with search results. By the end of this book, you'll have a basic understanding of how to build and deploy effective search and analytics solutions using Elasticsearch.
Table of Contents (10 chapters)

Best Practices

Elasticsearch is widely used, but that doesn't mean it's perfect. Elasticsearch projects can fail for any number of reasons, including Logstash node failure, the presence of too many shards, aggregations that are too deep, and even failures due to poorly mapped indices. Let’s take a look at some of the most common causes of project failure, and how to avoid them. In this chapter, we will explain Elasticsearch best practices that we can apply to increase performance. Oftentimes, people install Elasticsearch and start using it with the default settings, which causes some performance issues, so it is advisable to tune Elasticsearch to get optimal output.

In this chapter, we are going to cover the following topics:

  • Failure to obtain the required data
  • The best cluster configuration approaches
  • Using index templates to save time
  • Using _msearch for e-commerce...