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Mastering Apache Spark 2.x

You're reading from   Mastering Apache Spark 2.x Advanced techniques in complex Big Data processing, streaming analytics and machine learning

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Product type Paperback
Published in Jul 2017
Publisher Packt
ISBN-13 9781786462749
Length 354 pages
Edition 2nd Edition
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Author (1):
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Romeo Kienzler Romeo Kienzler
Author Profile Icon Romeo Kienzler
Romeo Kienzler
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Table of Contents (15) Chapters Close

Preface 1. A First Taste and What’s New in Apache Spark V2 FREE CHAPTER 2. Apache Spark SQL 3. The Catalyst Optimizer 4. Project Tungsten 5. Apache Spark Streaming 6. Structured Streaming 7. Apache Spark MLlib 8. Apache SparkML 9. Apache SystemML 10. Deep Learning on Apache Spark with DeepLearning4j and H2O 11. Apache Spark GraphX 12. Apache Spark GraphFrames 13. Apache Spark with Jupyter Notebooks on IBM DataScience Experience 14. Apache Spark on Kubernetes

Bare metal, virtual machines, and containers

It turns out that until the late 1990s, most of IT applications were deployed to bare metal machines. This means that you used some sort of server hardware and installed an operating system on it, and on top of that, your applications were installed.

But virtual machines are quite old. In fact, by the early 1960s, IBM was capable of running virtual machines on their mainframes, but it took decades until virtual machines experienced huge market adoption. Most likely, the reason for this was that consumer grade hardware was not powerful enough to run virtual systems efficiently. However, as we all know, this has changed dramatically.

Nowadays, a modern server can run hundreds of virtual machines and thousands of containers, but let's have a look at one after the other. So how do virtual machines work? In the following section, we...

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