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)

Performance Tuning

In this chapter, we will look into Elasticsearch performance-related issues and how we can tweak Elasticsearch to get the maximum output. Elasticsearch is widely used to search through a database and return documents that match the query, but it can quickly become overwhelmed when it has to retrieve a large number of documents using a single query. The Scroll API is therefore recommended in these situations. Elasticsearch does not index documents larger than 100 MB, but this setting can be changed in http.max_content_length as long as it does not go over the Lucene limit of 2 GB. Generally, users are recommended to avoid using large documents in Elasticsearch, as they put stress on the network and overwhelm memory usage and disk space.

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

  • Data sparsity
  • Solutions to common problems
  • How to tune for indexing...