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  • Book Overview & Buying Elasticsearch 5.x Cookbook
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Elasticsearch 5.x Cookbook

Elasticsearch 5.x Cookbook

By : Alberto Paro
2.5 (4)
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Elasticsearch 5.x Cookbook

Elasticsearch 5.x Cookbook

2.5 (4)
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. This book is your one-stop guide to master the complete Elasticsearch ecosystem. We’ll guide you through comprehensive recipes on what’s new in Elasticsearch 5.x, showing you how to create complex queries and analytics, and perform index mapping, aggregation, and scripting. Further on, you will explore the modules of Cluster and Node monitoring and see ways to back up and restore a snapshot of an index. You will understand how to install Kibana to monitor a cluster and also to extend Kibana for plugins. Finally, you will also see how you can integrate your Java, Scala, Python, and Big Data applications such as Apache Spark and Pig with Elasticsearch, and add enhanced functionalities with custom plugins. By the end of this book, you will have an in-depth knowledge of the implementation of the Elasticsearch architecture and will be able to manage data efficiently and effectively with Elasticsearch.
Table of Contents (25 chapters)
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Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Dedication
Preface

Executing geo distance aggregations


Among the other standard types that we have seen in the previous aggregations, Elasticsearch allows for executing aggregations against a GeoPoint: the geo distance aggregations. This is an evolution of the previous discussed range aggregations built to work on geo locations.

Getting ready

You need an up-and-running Elasticsearch installation, as we described in the Downloading and installing Elasticsearch recipe in Chapter 2, Downloading and Setup.

To execute curl via the command-line, you need to install curl for your operative system.

To correctly execute the following command, you need an index populated with the script (chapter_08/populate_aggregations.sh) available in the online code.

How to do it...

For executing geo distance aggregations, we will perform the following steps:

  1. Using the position field available in the documents, we want to aggregate the other documents in five ranges:

    • Less than 10 kilometers

    • From 10 kilometers to 20

    • From 20 kilometers to 50...

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