Book Image

Learning Elasticsearch

By : Abhishek Andhavarapu
Book Image

Learning Elasticsearch

By: Abhishek Andhavarapu

Overview of this book

Elasticsearch is a modern, fast, distributed, scalable, fault tolerant, and open source search and analytics engine. You can use Elasticsearch for small or large applications with billions of documents. It is built to scale horizontally and can handle both structured and unstructured data. Packed with easy-to- follow examples, this book will ensure you will have a firm understanding of the basics of Elasticsearch and know how to utilize its capabilities efficiently. You will install and set up Elasticsearch and Kibana, and handle documents using the Distributed Document Store. You will see how to query, search, and index your data, and perform aggregation-based analytics with ease. You will see how to use Kibana to explore and visualize your data. Further on, you will learn to handle document relationships, work with geospatial data, and much more, with this easy-to-follow guide. Finally, you will see how you can set up and scale your Elasticsearch clusters in production environments.
Table of Contents (11 chapters)
10
Exploring Elastic Stack (Elastic Cloud, Security, Graph, and Alerting)

Complex data types

In the previous section, we talked about simple data types. In this section, we will talk about how to set mapping for arrays, objects, and nested objects.

Array

There is no special data type for an array. A field can contain one or more fields of the same data type. Let's look at an example where we have two documents, as shown next:

Document 1:

{ "keyword_field" : "keyword1" }

Document 2:

{
"keyword_field" : ["keyword2", "keyword3"]
}

The mapping for keyword_field is defined as shown next:

{
"properties": {
"keyword_field": {
"type": "keyword"
}
}
}

No special handling is required for arrays...