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Mastering Apache Spark 2.x - Second Edition

You're reading from  Mastering Apache Spark 2.x - Second Edition

Product type Book
Published in Jul 2017
Publisher Packt
ISBN-13 9781786462749
Pages 354 pages
Edition 2nd Edition
Languages
Toc

Table of Contents (21) Chapters close

Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. A First Taste and What’s New in Apache Spark V2 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

Example--Apache Spark on Kubernetes


This example is taken directly from the Kubernetes GitHub page, which can be found at https://github.com/Kubernetes/Kubernetes/tree/master/examples/spark. We've done some modification to that example, since we are using a very specific Kubernetes deployment called Minikube. But we still want it to be based on the original example, since when you are using this link, you are guaranteed to always obtain an updated version compatible with the latest Kubernetes version in place. So these are the required steps, which are explained in detail in the next sections:

  1. Install Minikube local Kubernetes to your machine.
  2. Deploy the Apache Spark master node.
  3. Deploy the Apache Spark worker nodes.
  4. Deploy the Apache Kubernetes notebook application and test the whole cluster (optional).

The following section describes the prerequisites to run the example on your own.

Prerequisites

In order to get started quickly, it is highly recommended to either use one of the existing cloud...

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