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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
Author Profile Icon Tomcy John
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

Data Lake for other activities

With Data Lake and its huge and expensive infrastructure (in production deployment, ideally we use high-end machines and not commodity hardware), there are potential other uses for which it could be used. The main challenge with high end infrastructure is its effective utilization. While a high end infrastructure may be required for solving a problem, it may not be effectively utilized at all times. This is where we need to think of mechanisms that can help us extract required utilization of the infrastructure.

One of the most practical ways to do this is via multi-tenancy of the Hadoop infrastructure. If we look at Hadoop or any storage systems, there are two fundamental actions performed at the storage layer; one is to read and the other is to write the data for the purpose of data storage and processing.

This can be achieved at a basic level by leveraging security mechanisms...

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