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Data Lake for Enterprises

You're reading from   Data Lake for Enterprises Lambda Architecture for building enterprise data systems

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Product type Paperback
Published in May 2017
Publisher Packt
ISBN-13 9781787281349
Length 596 pages
Edition 1st Edition
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Authors (3):
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Pankaj Misra Pankaj Misra
Author Profile Icon Pankaj Misra
Pankaj Misra
Tomcy John Tomcy John
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Tomcy John
Vivek Mishra Vivek Mishra
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Vivek Mishra
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Toc

Table of Contents (13) Chapters Close

Preface 1. Introduction to Data FREE CHAPTER 2. Comprehensive Concepts of a Data Lake 3. Lambda Architecture as a Pattern for Data Lake 4. Applied Lambda for Data Lake 5. Data Acquisition of Batch Data using Apache Sqoop 6. Data Acquisition of Stream Data using Apache Flume 7. Messaging Layer using Apache Kafka 8. Data Processing using Apache Flink 9. Data Store Using Apache Hadoop 10. Indexed Data Store using Elasticsearch 11. Data Lake Components Working Together 12. Data Lake Use Case Suggestions

Flume event - Stream Data


Event is the unit of data which is send across the Flume pipeline. The structure of the event is quite simple and had two parts to it namely:

  • Event header: A Key/Value pair in the form Map<String, String>. These headers are meant to add more data about the event. For example, these headers can hold severity and priority aspects of this event, and so on. These headers can also contain UUID or event ID which distinguishes one event from the other.
  • Event payload: An array of bytes (byte array) in the form byte[]. 32 KB is the default body size, which is usually truncated after that figure but this is a configurable value in Flume.

This figure shows the internal structure of the Flume event, which hops from one agent to another in Flume:

Figure 13: Anatomy of a Flume event

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