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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

Goals and benefits


Similar to wholesalers, public Cloud providers base their business model on mass acquisition of IT resources, which are made available to Cloud consumers for attractive prices. This helps organizations to access powerful infrastructure without any infrastructure costs.

The most common economic rationale for investing in Cloud-based IT resources is to reduce initial IT investments, such as hardware, software purchases, and ownership costs. A cloud's measured usage characteristic represents a feature set that allows measured operational expenditures (directly related to business performance) to replace anticipated capital expenditures. This is also referred to as proportional cost.

The reduction of costs allow enterprises to start small, to increase IT resource allocation as needed. Moreover, lower initial expenses allow for capital to be redirected to core business investments. Opportunities to decrease costs are derived from the deployment and operation of large-scale data...

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