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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

Technology overview for Lambda Architecture


As explained briefly earlier, Lambda Architecture is a pattern with well defined guidelines and is technology agnostic. Looking at its various components/layer, any technology can be brought in to do the required job.

With, emergence of various cloud providers, you could even get ready-made components in cloud (many are cloud dependent) which actually implements the Lambda Architecture. In this book, we are marching ahead to actually create a Data Lake in which the lambda pattern just covers one layer, called Lambda Layer.

Since there are so many choices for technologies, the future chapters are a bit opinionated. When we make each technology, we would give the rationale for our choice, but keeping it as open as possible. We would also give our other technology choices, so that if needed, these technologies can indeed be swapped by the reader if required. Having said that, we will actually implement the Data Lake using the selected technology. The...

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