Book Image

Elasticsearch Server - Third Edition

By : Rafal Kuc
Book Image

Elasticsearch Server - Third Edition

By: Rafal Kuc

Overview of this book

ElasticSearch is a very fast and scalable open source search engine, designed with distribution and cloud in mind, complete with all the goodies that Apache Lucene has to offer. ElasticSearch’s schema-free architecture allows developers to index and search unstructured content, making it perfectly suited for both small projects and large big data warehouses, even those with petabytes of unstructured data. This book will guide you through the world of the most commonly used ElasticSearch server functionalities. You’ll start off by getting an understanding of the basics of ElasticSearch and its data indexing functionality. Next, you will see the querying capabilities of ElasticSearch, followed by a through explanation of scoring and search relevance. After this, you will explore the aggregation and data analysis capabilities of ElasticSearch and will learn how cluster administration and scaling can be used to boost your application performance. You’ll find out how to use the friendly REST APIs and how to tune ElasticSearch to make the most of it. By the end of this book, you will have be able to create amazing search solutions as per your project’s specifications.
Table of Contents (18 chapters)
Elasticsearch Server Third Edition
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Preface
Index

Chapter 5. Extending Your Index Structure

We started the previous chapter by learning how to deal with revised filtering in Elasticsearch 2.x and what to expect from it now. We also explored highlighting and how it can help us in improving the users' search experience. We discovered query validation in Elasticsearch and learned the ways of data sorting in Elasticsearch. Finally, we discussed query rewriting and how that affects our queries. By the end of this chapter, you will have learned the following topics:

  • Indexing tree-like structures

  • Indexing data that is not flat

  • Handling document relationships by using nested object and parent–child features

  • Modifying index structure by using Elasticsearch API