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ElasticSearch Cookbook - Second Edition

You're reading from ElasticSearch Cookbook - Second Edition Over 130 advanced recipes to search, analyze, deploy, manage, and monitor data effectively with ElasticSearch

Product type Paperback

Published in Jan 2015

Publisher

ISBN-13 9781783554836

Length 472 pages

Edition 2nd Edition

Languages

Java

Tools

Elasticsearch

Concepts

Enterprise Search

Author (1):

Alberto Paro

View More author details

Table of Contents (14) Chapters

Preface

1. Getting Started

2. Downloading and Setting Up FREE CHAPTER

3. Managing Mapping

4. Basic Operations

5. Search, Queries, and Filters

6. Aggregations

7. Scripting

8. Rivers

9. Cluster and Node Monitoring

10. Java Integration

11. Python Integration

12. Plugin Development

Index

Chapter 4. Basic Operations

In this chapter, we will cover:

Creating an index
Deleting an index
Opening/closing an index
Putting a mapping in an index
Getting a mapping
Deleting a mapping
Refreshing an index
Flushing an index
Optimizing an index
Checking if an index or type exists
Managing index settings
Using index aliases
Indexing a document
Getting a document
Deleting a document
Updating a document
Speeding up atomic operations (bulk operations)
Speeding up GET operations (multi GET)

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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