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

Chapter 3. Basic Concepts of Mapping

In the previous chapter, we talked about the nature of the Elasticsearch index. We started by looking at the basic concept and we discussed mapping. We talked about index flexibility and data denormalization. Finally, we discussed about inverted index and how the data is organized in an inverted index. In this chapter, we will continue to discuss mapping. We will first go through basic concepts. Then we'll focus on the relationship between mapping and relevant search results. Lastly, we will try to have a good grasp on schema-less. At the end of this chapter, we will have covered the following topics:

  • What are metadata fields?

  • How to control document metadata?

  • What data types are?

  • The relationship between mapping and getting relevant search results

  • What is the meaning of schema-less?