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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

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In the modern world, an increasing number of people are becoming interconnected to one another via the internet. With the advent of the smartphone, this trend has skyrocketed. Nowadays, the smartphone can be used to do many things, such as check social media, order food online, and call a cab online. We are finding ourselves more reliant on the internet than ever before, and we will only become more reliant in the future. With this development comes a massive increase in data generation. As the internet began to boom, the very nature of data processing changed. Any time one of the apps or service is accessed on the phone, real-time data processing is taking place. Because there is a lot at stake in terms of the quality of their applications, companies are forced to improve data processing, and with improvements come paradigm shifts. One paradigm that is currently being researched and used is the idea of a highly scalable, real-time (or as close to real-time as possible) processing...

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