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Modern Big Data Processing with Hadoop

You're reading from  Modern Big Data Processing with Hadoop

Product type Book
Published in Mar 2018
Publisher Packt
ISBN-13 9781787122765
Pages 394 pages
Edition 1st Edition
Languages
Concepts
Authors (3):
V Naresh Kumar V Naresh Kumar
Profile icon V Naresh Kumar
Manoj R Patil Manoj R Patil
Profile icon Manoj R Patil
Prashant Shindgikar Prashant Shindgikar
Profile icon Prashant Shindgikar
View More author details

Table of Contents (12) Chapters

Preface 1. Enterprise Data Architecture Principles 2. Hadoop Life Cycle Management 3. Hadoop Design Consideration 4. Data Movement Techniques 5. Data Modeling in Hadoop 6. Designing Real-Time Streaming Data Pipelines 7. Large-Scale Data Processing Frameworks 8. Building Enterprise Search Platform 9. Designing Data Visualization Solutions 10. Developing Applications Using the Cloud 11. Production Hadoop Cluster Deployment

Flume

Flume is a reliable, available and distributed service to efficiently collect, aggregate, and transport large amounts of log data. It has a flexible and simple architecture that is based on streaming data flows. The current version of Apache Flume is 1.7.0, which was released in October 2016.

Apache Flume architecture

The following diagram depicts the architecture of Apache Flume:

Let's take a closer look at the components of the Apache Flume architecture:

  • Event: An event is a byte payload with optional string headers. It represents the unit of data that Flume can carry from its source to destination.
  • Flow: The transport of events from source to destination is considered a data flow, or just flow.
  • Agent: It is...
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