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Modern Big Data Processing with Hadoop

You're reading from   Modern Big Data Processing with Hadoop Expert techniques for architecting end-to-end big data solutions to get valuable insights

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Product type Paperback
Published in Mar 2018
Publisher Packt
ISBN-13 9781787122765
Length 394 pages
Edition 1st Edition
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Concepts
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Authors (3):
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Manoj R Patil Manoj R Patil
Author Profile Icon Manoj R Patil
Manoj R Patil
Prashant Shindgikar Prashant Shindgikar
Author Profile Icon Prashant Shindgikar
Prashant Shindgikar
V Naresh Kumar V Naresh Kumar
Author Profile Icon V Naresh Kumar
V Naresh Kumar
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Toc

Table of Contents (12) Chapters Close

Preface 1. Enterprise Data Architecture Principles 2. Hadoop Life Cycle Management FREE CHAPTER 3. Hadoop Design Consideration 4. Data Movement Techniques 5. Data Modeling in Hadoop 6. Designing Real-Time Streaming Data Pipelines 7. Large-Scale Data Processing Frameworks 8. Building Enterprise Search Platform 9. Designing Data Visualization Solutions 10. Developing Applications Using the Cloud 11. Production Hadoop Cluster Deployment

Developing Applications Using the Cloud

In the early days of computing, CPU power and storage were very scarce, and so the cost of purchasing relevant equipment was very high. With the advances in the development of personal computing in the early 80s by Apple and Microsoft, more and more individuals and organizations have gained access to these computing devices. As the industry has developed the way chips are made and billions if not trillions of transistors are now put on single chips, the size of these computing devices has drastically reduced, from taking up entire rooms to comprising a single unit of a rack in the data center. When the computation speed and storage device capacity started increasing, individuals and enterprises started to realize that efficiently managing their computing resources was becoming a challenge.

The widespread use of the internet has also made...

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