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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

Elasticsearch 5.x introduces a set of powerful functionalities, targeting the problems that arise during ingestion of documents via the ingest node.

An Elasticsearch node can be master, data, or ingest.

The idea to split the ingest component from the others, is to create a more stable cluster due to problems that can arise during pre-processing documents.

To create a more stable cluster, the ingest nodes should be isolated by the master or data nodes, in the event that some problems may occur, such as a crash due to an attachment plugin and high loads due to complex type manipulation.

Note

The ingestion node can replace a Logstash installation in simple scenarios.

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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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