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Elasticsearch 8.x Cookbook - Fifth Edition

You're reading from Elasticsearch 8.x Cookbook - Fifth Edition

Product type Book

Published in May 2022

Publisher Packt

ISBN-13 9781801079815

Pages 750 pages

Edition 5th Edition

Languages

Concepts

Enterprise Search

Author (1):

Alberto Paro

Table of Contents (20) Chapters

Preface

Chapter 1: Getting Started

Chapter 2: Managing Mappings

Chapter 3: Basic Operations

Chapter 4: Exploring Search Capabilities

Chapter 5: Text and Numeric Queries

Chapter 6: Relationships and Geo Queries

Chapter 7: Aggregations

Chapter 8: Scripting in Elasticsearch

Chapter 9: Managing Clusters

Chapter 10: Backups and Restoring Data

Chapter 11: User Interfaces

Chapter 12: Using the Ingest Module

Chapter 13: Java Integration

Chapter 14: Scala Integration

Chapter 15: Python Integration

Chapter 16: Plugin Development

Chapter 17: Big Data Integration

Chapter 18: X-Pack

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Creating an ingest plugin

Elasticsearch 5.x introduced the ingest node that allows the modification, via a pipeline, to the records before ingesting in Elasticsearch. We have already seen in Chapter 12, Using the Ingest Module, that a pipeline is composed of one or more processor actions. In this recipe, we will see how to create a custom processor that stores in a field the initial character of another one.

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.

Gradle or an integrated development environment (IDE) that supports Java programming with Gradle (version 7.3.x used in the examples), such as Eclipse, Visual Studio Code, or IntelliJ IDEA, is required. Java JDK 17 or above needs to be installed.

The code for this recipe is available in the ch16/ingest_plugin directory.

How to do it...

To create an ingest processor plugin, we need to create the...

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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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