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Apache Kafka 1.0 Cookbook

You're reading from   Apache Kafka 1.0 Cookbook Over 100 practical recipes on using distributed enterprise messaging to handle real-time data

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Product type Paperback
Published in Dec 2017
Publisher Packt
ISBN-13 9781787286849
Length 250 pages
Edition 1st Edition
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Authors (2):
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Raúl Estrada Raúl Estrada
Author Profile Icon Raúl Estrada
Raúl Estrada
Alexey Zinoviev Alexey Zinoviev
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Alexey Zinoviev
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Toc

Table of Contents (11) Chapters Close

Preface 1. Configuring Kafka FREE CHAPTER 2. Kafka Clusters 3. Message Validation 4. Message Enrichment 5. The Confluent Platform 6. Kafka Streams 7. Managing Kafka 8. Operating Kafka 9. Monitoring and Security 10. Third-Party Tool Integration

Pushing data from Kafka to Elastic


As mentioned, Elasticsearch is a distributed, full-text search engine that supports a RESTful web interface and schema-free JSON documents. Elasticsearch was built with distributed searches in mind. There are several ways to push data into Elasticsearch. In this recipe, the plugin that enables data pushing from Kafka to Elasticsearch is analyzed.

Getting ready

For this recipe, a Kafka cluster must be up and running and a confluent platform is needed. To install Elasticsearch follow the instructions on this page: https://www.elastic.co/guide/en/elasticsearch/reference/current/_installation.html.

How to do it...

The Elasticsearch connector is needed. Before starting the connector, the configuration is in

etc/kafka-connect-elasticsearch/quickstart-elasticsearch.properties.

This must be properly set to the Elasticsearch configuration: connection.url points to the correct HTTP address.

To start the Elasticsearch connector, use the following command:

$ ./bin/connect...
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