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Elasticsearch 7.0 Cookbook

You're reading from Elasticsearch 7.0 Cookbook Over 100 recipes for fast, scalable, and reliable search for your enterprise

Product type Paperback

Published in Apr 2019

Publisher Packt

ISBN-13 9781789956504

Length 724 pages

Edition 4th Edition

Languages

Java

Tools

Elasticsearch

Concepts

Enterprise Search

Author (1):

Alberto Paro

View More author details

Table of Contents (19) Chapters

Preface

1. Getting Started FREE CHAPTER

2. Managing Mapping

3. Basic Operations

4. Exploring Search Capabilities

5. Text and Numeric Queries

6. Relationship and Geo Queries

7. Aggregations

8. Scripting in Elasticsearch

9. Managing Clusters

10. Backups and Restoring Data

11. User Interfaces

12. Using the Ingest Module

13. Java Integration

14. Scala Integration

15. Python Integration

16. Plugin Development

17. Big Data Integration

18. Another Book You May Enjoy

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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 when using IP addresses, Elasticsearch provides the IPv4 and IPv6 type that can be used to store IP addresses 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 1, Getting Started.

How to do it...

You need to define the type of the field that contains...

The rest of the chapter is locked

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Authors (1)

Alberto Paro

Alberto Paro

Alberto Paro is an engineer, manager, and software developer. He currently works as technology architecture delivery associate director of the Accenture Cloud First data and AI team in Italy. He loves to study emerging solutions and applications, mainly related to cloud and big data processing, NoSQL, Natural language processing (NLP), software development, and machine learning. In 2000, he graduated in computer science engineering from Politecnico di Milano. Then, he worked with many companies, mainly using Scala/Java and Python on knowledge management solutions and advanced data mining products, using state-of-the-art big data software. A lot of his time is spent teaching how to effectively use big data solutions, NoSQL data stores, and related technologies.

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