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


In this chapter, we' looked at the important, main topics for efficient indexing and relevant search results: How to store documents? What is the difference between the storable and searchable field? What is the analysis process? What is the impact on the relevant search results? In addition to that, we've briefly discussed some of the basic concepts of Elasticsearch that are associated with Lucene (for example, inverted index and the _source field).

In the next chapter, you'll learn about the Elasticsearch index—what mapping is, what inverted index is, the denormalized data structure—and some other concepts related to this topic.