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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

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Product type Paperback
Published in Jan 2015
Publisher
ISBN-13 9781783554836
Length 472 pages
Edition 2nd Edition
Languages
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Author (1):
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Alberto Paro Alberto Paro
Author Profile Icon Alberto Paro
Alberto Paro
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Table of Contents (14) Chapters Close

Preface 1. Getting Started FREE CHAPTER 2. Downloading and Setting Up 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

Introduction

There are two ways to put your data into ElasticSearch. As you have seen in previous chapters, one way is to use the index API, which allows you to store documents in ElasticSearch via the PUT/POST API or the bulk API. The other way is to use a service that fetches the data from an external source (at one time or periodically) and puts it in the cluster.

ElasticSearch calls these services rivers, and the ElasticSearch community provides several rivers to connect to different data sources, as follows:

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

Rivers are available as external plugins at http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/modules-plugins.html#river, which provides an updated list of the available ElasticSearch rivers. In this chapter, we'll discuss how to manage a river (create, check, and delete) and how to configure the most common ones.

A river is a very handy tool to ingest data in ElasticSearch...

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