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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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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

Summary

As with other chapters in this part of the book, we covered the layer and its technology. We gave the reason this technology was chosen and then soon delved deep into the working of this technology, its architecture, its components and so on.

We then explained some of the important aspects of this technology and delved deep into an actual working example. We brought the SCV use case in conjunction with this technology; we closed off this chapter with sections detailing when and when not to use Elasticsearch and closing with other options that could be used in place of the chosen Elasticsearch.

This technology aspect in our Data Lake is significant, and we are sure it is one of the handy technology additions. With this technology detailed, we are almost done with this part of book. With this chapter, we have indeed covered almost all the technologies in our Data Lake; also we have now connected some...

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