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 1. Introduction to Efficient Indexing

Elasticsearch is an open source full text search engine and data analysis tool that was developed in Java, is Apache Lucene-based, and scalable. A huge scale of data is produced at every moment in today's world of information technologies, in social media, in video sharing sites, and in medium and large-sized companies that provide services in communication, health, security, and other areas. Here we are talking about an information/data ocean, and we call this ocean briefly as big data in the world of information technology. An important part of this world of big data is unstructured, scattered, and insignificant when it is in isolation.

For this reason, some requirements such as recording, accessing, analyzing, and processing of data are significant. Like similar search engines, Elasticsearch is one of the tools that have been developed to deal with the problems mentioned previously, which belong to the world of big data.

What should I look for—high efficiency and/or performance—when Elasticsearch is used for the purposes mentioned earlier?

This book will target experienced developers who have used Elasticsearch before and want to extend their knowledge about how to effectively perform Elasticsearch indexing. Therefore, this book assumes that the reader already knows the basic issues and concepts of Elasticsearch. For example, what is Elasticsearch, how to install it, what purposes it serves, and so on. This book in your hand is intended to assist you with technical information and concrete applications about efficient indexing and relevant search result in Elasticsearch. This chapter aims to introduce and discuss the main topics for the purposes mentioned previously. To this end, we will look closely at how to store data by Elasticsearch and try to understand the document storage strategy. The relevant search result is closely related to data analysis. Hence, we will do an introduction to understanding the analysis process. In other chapters of this book, you will find the necessary discussions and examples for a better understanding of the following main issues:

  • How to store documents

  • The difference between the storable and searchable field

  • What the function of the analyzer is

  • How to improve relevant search results