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Elasticsearch 5.x Cookbook

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

Product type Paperback

Published in Feb 2017

Publisher

ISBN-13 9781786465580

Length 696 pages

Edition 3rd Edition

Languages

Java

Tools

Elasticsearch

Concepts

Enterprise Search

Author (1):

Alberto Paro

View More author details

Table of Contents (25) Chapters

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

Introduction

In the previous chapter, we saw how it is possible to use a native client to access the Elasticsearch server via Java. This chapter is dedicated to the Python language and how to manage common tasks via its clients.

Apart from Java, the Elasticsearch team supports official clients for Perl, PHP, Python, .NET, and, Ruby. (See the announcement post on the Elasticsearch blog at http://www.elasticsearch.org/blog/unleash-the-clients-ruby-python-php-perl/.) These clients have a lot of advantages over other implementations. A few of them are mentioned as follows:

They are strongly tied to the Elasticsearch API:

"These clients are direct translations of the native Elasticsearch REST interface" - The Elasticsearch team

They handle dynamic node detection and failover: they are built with a strong networking base for communicating with the cluster.
They have full coverage of...

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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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