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 basic concepts of mapping and reviewed the basic definitions—what the metadata fields are, how does mapping control them—and we examined some data types. Then we looked at the relationship between mapping and relevant search results. Finally, we tried to understand correctly the meaning of schema-less by asking the question: Is the claim about "Elasticsearch stands for the schema-free model" always true?

In the next chapter, you'll learn about the analysis module and analyzers. In addition, we will examine the questions—what is the analysis process? What do the underlying Tokenizer, Token, and CharFilters make?—and some other concepts related to this topic.