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)

Querying Elasticsearch

One of most powerful features of Elasticsearch is the Query DSL (Domain specific Language) or the query language. The query language is very expressive and can be used to define filters, queries, sorting, pagination, and aggregations in the same query. To execute a search query, an HTTP request should be sent to the _search endpoint. The index and type on which the query should be executed is specified in the URL. Index and type are optional. If no index/type is specified, Elasticsearch executes the request across all the indexes in the cluster. A search query in Elasticsearch can be executed in two different ways:

  • By passing the search request as query parameters.
  • By passing the search request in the request body.

A simple search query using query parameters is shown here:

GET chapter6/product/_search?q=product_name:jacket

Simple queries can be executed...