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Elasticsearch 5.x Cookbook

You're reading from   Elasticsearch 5.x Cookbook Distributed Search and Analytics

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Product type Paperback
Published in Feb 2017
Publisher
ISBN-13 9781786465580
Length 696 pages
Edition 3rd Edition
Languages
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Author (1):
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Alberto Paro Alberto Paro
Author Profile Icon Alberto Paro
Alberto Paro
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Table of Contents (25) Chapters Close

Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Dedication
Preface
1. Getting Started FREE CHAPTER 2. Downloading and Setup 3. Managing Mappings 4. Basic Operations 5. Search 6. Text and Numeric Queries 7. Relationships and Geo Queries 8. Aggregations 9. Scripting 10. Managing Clusters and Nodes 11. Backup and Restore 12. User Interfaces 13. Ingest 14. Java Integration 15. Scala Integration 16. Python Integration 17. Plugin Development 18. Big Data Integration

Mapping an IP field


Elasticsearch is used in a lot of systems to collect and search logs such as Kibana (https://www.elastic.co/products/kibana) and LogStash (https://www.elastic.co/products/logstash). To improve search in these scenarios, it provides the IPv4 and IPv6 type that can be used to store IP address in an optimized way.

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.

How to do it...

You need to define the type of the field that contains IP address as ip  as follows:

Using the preceding order example, we can extend it adding the customer IP with:

 "customer_ip": { 
 "type": "ip", 
 "store": "yes" 
   } 

The IP must be in the standard point notation form, that is:

"customer_ip":"19.18.200.201" 

How it works...

When Elasticsearch is processing a document, if a field is an IP one, it tries to convert its value to a numerical form and generate...

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