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

Templates and dynamic templates


In the Mappings configuration section of Chapter 2, Indexing Your Data, we discussed mappings, how they are created, and how the type-determining mechanism works. Now we will get into more advanced topics. We will show you how to dynamically create mappings for new indices and how to apply some logic to the templates, so that new indices are already created with predefined mappings.

Templates

In various parts of the book, when discussing index configuration and its structure, we've seen that this can become complicated, especially when we have sophisticated data structures that we want to index, search, and aggregate. Especially if you have a lot of similar indices, taking care of the mappings in each of them can be a very painful process – each new index has to be created with appropriate mappings. Elasticsearch creators predicted this and implemented a feature called index templates. Each template defines a pattern, which is compared to a newly created index...