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Apache Hadoop 3 Quick Start Guide

You're reading from   Apache Hadoop 3 Quick Start Guide Learn about big data processing and analytics

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Product type Paperback
Published in Oct 2018
Publisher Packt
ISBN-13 9781788999830
Length 220 pages
Edition 1st Edition
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Author (1):
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Hrishikesh Vijay Karambelkar Hrishikesh Vijay Karambelkar
Author Profile Icon Hrishikesh Vijay Karambelkar
Hrishikesh Vijay Karambelkar
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Table of Contents (10) Chapters Close

Preface 1. Hadoop 3.0 - Background and Introduction FREE CHAPTER 2. Planning and Setting Up Hadoop Clusters 3. Deep Dive into the Hadoop Distributed File System 4. Developing MapReduce Applications 5. Building Rich YARN Applications 6. Monitoring and Administration of a Hadoop Cluster 7. Demystifying Hadoop Ecosystem Components 8. Advanced Topics in Apache Hadoop 9. Other Books You May Enjoy

Writing Flume jobs

Apache Flume offers the service to feed logs containing unstructured information back to Hadoop. Flume works across any type of data source. Flume can receive both log data or continuous event data, and it consumes events, incremental logs from sources such as the application server, and social media events.

The following diagram illustrates how Flume works. When flume receives an event, it is persisted in a channel (or data store), such as a local file system, before it is removed and pushed to the target by Sink. In the case of Flume, a target can be HDFS storage, Amazon S3, or another custom application:

Flume also supports multipleFlume agents, as shown in the preceding data flow. Data can be collected, aggregated together, and then processed through a multi-agent complex workflow that is completely customizable by the end user. Flume provides message reliability...

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