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)

Using cURL or Postman

The primary way of interacting with Elasticsearch is using the REST API over HTTP. If Kibana or Sense is not an option for you, you can use any of the popular HTTP clients, such as cURL or Postman. Curl is a command line-based client available on most operating systems. Postman is an UI-based HTTP client available for major operating systems. You can get postman from the following link:

https://www.getpostman.com/

To execute the queries in this book using other HTTP clients, you have to specify the Elasticsearch server address (such as http://127.0.0.1:9200) in front of the API endpoint to execute the query. Let's take an example query found in this book:

 POST es-index/_search
{
"query": {
"match_all": {}
}
}

To execute the preceding query in cURL, you should add the curl command and the -d flag and wrap the query in...