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ElasticSearch Cookbook

You're reading from ElasticSearch Cookbook As a user of ElasticSearch in your web applications you'll already know what a powerful technology it is, and with this book you can take it to new heights with a whole range of enhanced solutions from plugins to scripting.

Product type Paperback

Published in Dec 2013

Publisher Packt

ISBN-13 9781782166627

Length 422 pages

Edition 1st 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 FREE CHAPTER

2. Downloading and Setting Up ElasticSearch

3. Managing Mapping

4. Standard Operations

5. Search, Queries, and Filters

6. Facets

7. Scripting

8. Rivers

9. Cluster and Nodes Monitoring

10. Java Integration

11. Python Integration

12. Plugin Development

Index

Introduction

There are two ways to insert your data in ElasticSearch. In the previous chapters we have seen the index API, which allows storing documents in ElasticSearch via the PUT/POST API or the bulk shortcut. The other way is to use a service that fetches the data from an external source (one shot or periodically) and puts the data into the cluster.

ElasticSearch names these services as Rivers and the ElasticSearch community provides several rivers to connect to the following data sources:

CouchDB
MongoDB
RabbitMQ
SQL DBMS (Oracle, MySQL, PostgreSQL and so on)
Redis
Twitter
Wikipedia

The rivers are available as external plugins.

In this chapter we'll discuss how to manage a river (creating, checking, and deleting) and how to configure the most common ones.

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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