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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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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

Sqoop working example


We will be using Google Cloud Platform for running the whole use case that we will be covering in this book. Screenshots and code would be covered throughout this book with this in mind so that the reader at the end of this book would have a fully functioning Data Lake in the cloud which slowly could be connected to the real database existing in the enterprise.

Being the first chapter, which is now dealing with installation and code, this chapter will install certain softwares/tools/technologies/libraries that will be referred to in subsequent chapters. In the context of Sqoop, some installations and commands won't be required butare needed for running all of these in the cloud having a clean node with nothing installed on it.

These examples have been prepared and tested on CentOS 7, and this would be our platform for all the examples covered in this book.

Installation and Configuration

For all the installations discussed in this book, we are following some basic conventions...

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