Book Image

Elasticsearch 7.0 Cookbook - Fourth Edition

By : Alberto Paro
Book Image

Elasticsearch 7.0 Cookbook - Fourth Edition

By: Alberto Paro

Overview of this book

Elasticsearch is a Lucene-based distributed search server that allows users to index and search unstructured content with petabytes of data. With this book, you'll be guided through comprehensive recipes on what's new in Elasticsearch 7, and see how to create and run complex queries and analytics. Packed with recipes on performing index mapping, aggregation, and scripting using Elasticsearch, this fourth edition of Elasticsearch Cookbook will get you acquainted with numerous solutions and quick techniques for performing both every day and uncommon tasks such as deploying Elasticsearch nodes, integrating other tools to Elasticsearch, and creating different visualizations. You will install Kibana to monitor a cluster and also extend it using a variety of plugins. Finally, you will integrate your Java, Scala, Python, and big data applications such as Apache Spark and Pig with Elasticsearch, and create efficient data applications powered by enhanced functionalities and custom plugins. By the end of this book, you will have gained in-depth knowledge of implementing Elasticsearch architecture, and you'll be able to manage, search, and store data efficiently and effectively using Elasticsearch.
Table of Contents (23 chapters)
Title Page

Using the geo_distance query

When you are working with geo locations, one common task is to filter results based on the distance from a location. This scenario covers very common site requirements, such as the following:

  • Finding the nearest restaurant within a distance of 20 km
  • Finding my nearest friends within a range of 10 km

The geo_distance query is used to achieve this goal.

Getting ready

You need an up and running Elasticsearch installation, as we described in the Downloading and installing Elasticsearch recipe in Chapter 1Getting Started.

To execute these commands, any HTTP client can be used, such as curl (https://curl.haxx.se/), Postman (https://www.getpostman.com/), or similar. I suggest using the Kibana...