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Elasticsearch 7.0 Cookbook. - Fourth Edition

You're reading from Elasticsearch 7.0 Cookbook. - Fourth Edition

Product type Book

Published in Apr 2019

Publisher Packt

ISBN-13 9781789956504

Pages 724 pages

Edition 4th Edition

Languages

Concepts

Enterprise Search

Author (1):

Alberto Paro

Table of Contents (23) Chapters

Title Page

Copyright and Credits

Elasticsearch 7.0 Cookbook Fourth Edition

About Packt

Contributors

Preface

1. Getting Started

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

1. Another Book You May Enjoy

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Managing Kibana discovery

One of the most popular aspects of Kibana is the discovery dashboard. This is because it allows you to dynamically navigate your data. With the evolution of Kibana, a lot of new features have been added to the Discovery dashboard in order to allow you to easily filter and analyze your data.

Getting ready

You will need an up-and-running Elasticsearch installation – similar to the one that we described in the Downloading and installing Elasticsearch recipe in Chapter 1, Getting Started. Additionally, a working Kibana instance is required, as described in the Installing Kibana recipe of this chapter.

If you have used Docker Compose, which is available in the ch01 directory...

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Authors (1)

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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