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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
Author Profile Icon Vivek Mishra
Vivek Mishra
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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

When to use Flume


Some of the consideration which you can use when choosing Flume for handling different use cases is as follows - choose Flume when you want:

  • To acquire data from a variety of source and store into Hadoop system
  • To handle high-velocity and high-volume data into Hadoop system
  • Reliable delivery of data to the destination
  • A scalable solution that can run quite easily just by adding more machine to it, when the velocity and volume of data increases
  • The capability of dynamically configuring the various components in the architecture without incurring any downtime.
  • To achieve a single point of contact for all the various configurations based on which the overall architecture is functioning
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