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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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Creating a client

The official Elasticsearch clients are designed to manage a lot of issues that are typically required to create solid REST clients, such as retry if there are network issues, autodiscovery of other nodes of the cluster, and data conversions for communicating on the HTTP layer.

In this recipe, we'll learn how to instantiate a client with varying options.

Getting ready

You need an up-and-running Elasticsearch installation, which we described how to get in the Downloading and installing Elasticsearch recipe in Chapter 1, Getting Started.

A Python 2.x or 3.x distribution should be installed. In Linux and the Mac OS X system, it's already provided in the standard installation...

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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