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)

Mapping the same field with different mappings

Sometimes you want to index the same field with different mappings. For example, you want to index the title field both as text and as keyword. You can use the keyword field for an exact match and the text field for text search. You can do this by defining two fields, one with keyword mapping and other with text mapping, as shown next:

{
"properties": {
"title_text": {
"type": "text"
},
"title_keyword": {
"type": "keyword"
}
}
}

You can index the document as follows:

{
"title_text" : "Learning Elasticsearch",
"title_keyword" : "Learning Elasticsearch"
}

While indexing, the same value is used for both the title_text and title_keyword fields. The document source will now have two fields with...