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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

Cloud characteristics


An IT environment requires a specific set of characteristics to enable the remote provisioning of scalable and measured IT resources in an effective manner. These characteristics need to exist to a meaningful extent for the IT environment to be considered an effective Cloud.

The following six specific characteristics are common to the majority of Cloud environments:

  • On-demand usage
  • Ubiquitous access
  • Multitenancy (and resource pooling)
  • Elasticity
  • Measured usage
  • Resiliency

On-demand usage

A Cloud consumer can unilaterally access Cloud-based IT resources, giving the Cloud consumer the freedom to self-provision these IT resources. Once configured, usage of the self-provisioned IT resources can be automated, reducing human involvement with the Cloud consumer or Cloud provider. This results in an on-demand usage environment. Also known as on-demand self-service usage, this characteristic enables the service-based and usage-driven features found in mainstream Clouds.

Ubiquitous access...

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