Book Image

Elasticsearch Indexing

By : Huseyin Akdogan
Book Image

Elasticsearch Indexing

By: Huseyin Akdogan

Overview of this book

Beginning with an overview of the way ElasticSearch stores data, you’ll begin to extend your knowledge to tackle indexing and mapping, and learn how to configure ElasticSearch to meet your users’ needs. You’ll then find out how to use analysis and analyzers for greater intelligence in how you organize and pull up search results – to guarantee that every search query is met with the relevant results! You’ll explore the anatomy of an ElasticSearch cluster, and learn how to set up configurations that give you optimum availability as well as scalability. Once you’ve learned how these elements work, you’ll find real-world solutions to help you improve indexing performance, as well as tips and guidance on safety so you can back up and restore data. Once you’ve learned each component outlined throughout, you will be confident that you can help to deliver an improved search experience – exactly what modern users demand and expect.
Table of Contents (15 chapters)
Elasticsearch Indexing
About the Author
About the Reviewer


When you create an index, Elasticsearch subdivides your index into multiple Lucene indices that are called shards. The process of this subdividing is called sharding. Shards are automatically managed by Elasticsearch and are in themselves a fully functional and independent index. You can define a number of shards. By default, a shard is being refreshed per second. Elasticsearch thus supports real-time search. Shards are useful when working with large data because when you have a large index, disk capacity of a single node may not be sufficient or may be too slow to serve search requests. Shards solve such, and similar, problems and allow you to horizontally scale your content volume.