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Big Data Analytics with Hadoop 3

You're reading from   Big Data Analytics with Hadoop 3 Build highly effective analytics solutions to gain valuable insight into your big data

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Product type Paperback
Published in May 2018
Publisher Packt
ISBN-13 9781788628846
Length 482 pages
Edition 1st Edition
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Author (1):
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Sridhar Alla Sridhar Alla
Author Profile Icon Sridhar Alla
Sridhar Alla
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Table of Contents (13) Chapters Close

Preface 1. Introduction to Hadoop FREE CHAPTER 2. Overview of Big Data Analytics 3. Big Data Processing with MapReduce 4. Scientific Computing and Big Data Analysis with Python and Hadoop 5. Statistical Big Data Computing with R and Hadoop 6. Batch Analytics with Apache Spark 7. Real-Time Analytics with Apache Spark 8. Batch Analytics with Apache Flink 9. Stream Processing with Apache Flink 10. Visualizing Big Data 11. Introduction to Cloud Computing 12. Using Amazon Web Services

Distributed computing using Apache Hadoop

We are surrounded by devices such as the smart refrigerator, smart watch, phone, tablet, laptops, kiosks at the airport, ATMs dispensing cash to you, and many many more, with the help of which we are now able to do things that were unimaginable just a few years ago. We are so used to applications such as Instagram, Snapchat, Gmail, Facebook, Twitter, and Pinterest that it is next to impossible to go a day without access to such applications. Today, cloud computing has introduced us to the following concepts:

  • Infrastructure as a Service
  • Platform as a Service
  • Software as a Service

Behind the scenes is the world of highly scalable distributed computing, which makes it possible to store and process Petabytes (PB) of data:

  • 1 EB = 1024 PB (50 million Blu-ray movies)
  • 1 PB = 1024 TB (50,000 Blu-ray movies)
  • 1 TB = 1024 GB (50 Blu-ray movies...
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