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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

Learning by example

Let's have a look at an example in order to learn how to use this tool:

  1. If you don't have a Bluemix account, register for one here: ibm.biz/CloudFreemium.
  2. Once you have an account in place, go to https://datascience.ibm.com, and click on Sign In.
  3. Click on Sign-In with your IBM ID, and follow the instructions.

Once you are ready to go, let's start with a small hello world project by creating a Jupyter notebook on Scala with Apache Spark 2.x.

As illustrated in the following screenshot, click on the Create notebook button:

This opens the Create notebook dialog as illustrated here:

So let's have a look at what information we need to provide:

  1. First of all, each notebook needs a name. We choose packt_hello_world as the name.
  2. Then we select Scala as the programming language.
  3. We want to run our code on an Apache Spark 2.x instance.
  4. We choose...
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