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Apache Flume: Distributed Log Collection for Hadoop

You're reading from Apache Flume: Distributed Log Collection for Hadoop

Product type Book

Published in Feb 2015

Publisher

ISBN-13 9781784392178

Pages 178 pages

Edition 1st Edition

Languages

Concepts

Data Processing

Author (1):

Steven Hoffman

Table of Contents (16) Chapters

Apache Flume: Distributed Log Collection for Hadoop Second Edition

Credits

About the Author

About the Reviewers

www.PacktPub.com

Preface

1. Overview and Architecture

2. A Quick Start Guide to Flume

3. Channels

4. Sinks and Sink Processors

5. Sources and Channel Selectors

6. Interceptors, ETL, and Routing

7. Putting It All Together

8. Monitoring Flume

9. There Is No Spoon – the Realities of Real-time Distributed Data Collection

Index

JMS source

Sometimes, data can originate from asynchronous message queues. For these cases, you can use Flume's JMS source to create events read from a JMS Queue or Topic. While it is theoretically possible to use any Java Message Service (JMS) implementation, Flume has only been tested with ActiveMQ, so be sure to test thoroughly if you use a different provider.

Like the previously covered ElasticSearch sink in Chapter 4, Sinks and Sink Processors, Flume does not come packaged with the JMS implementation you'll be using, as the versions need to match up, so you'll need to include the necessary implementation JAR files on the Flume agent's classpath. The preferred method is to use the --plugins-dir parameter mentioned in Chapter 2, A Quick Start Guide to Flume, which we'll cover in more detail in the next chapter.

Note

ActiveMQ is just one provider of the Java Message Service API. For more information, see the project homepage at http://activemq.apache.org.

To configure this source, set the...

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Authors (1)

Steven Hoffman

Steve Hoffman has 32 years of experience in software development, ranging from embedded software development to the design and implementation of large-scale, service-oriented, object-oriented systems. For the last 5 years, he has focused on infrastructure as code, including automated Hadoop and HBase implementations and data ingestion using Apache Flume. Steve holds a BS in computer engineering from the University of Illinois at Urbana-Champaign and an MS in computer science from DePaul University. He is currently a senior principal engineer at Orbitz Worldwide (http://orbitz.com/). More information on Steve can be found at http://bit.ly/bacoboy and on Twitter at @bacoboy. This is the first update to Steve's first book, Apache Flume: Distributed Log Collection for Hadoop, Packt Publishing.

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