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Learning Jupyter

You're reading from   Learning Jupyter Select, Share, Interact and Integrate with Jupyter Notebook

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Product type Paperback
Published in Nov 2016
Publisher Packt
ISBN-13 9781785884870
Length 238 pages
Edition 1st Edition
Languages
Tools
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Author (1):
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 Toomey Toomey
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Toomey
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Toc

Table of Contents (16) Chapters Close

Learning Jupyter
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface
1. Introduction to Jupyter FREE CHAPTER 2. Jupyter Python Scripting 3. Jupyter R Scripting 4. Jupyter Julia Scripting 5. Jupyter JavaScript Coding 6. Interactive Widgets 7. Sharing and Converting Jupyter Notebooks 8. Multiuser Jupyter Notebooks 9. Jupyter Scala 10. Jupyter and Big Data

Apache Spark


One of the tools we will be using is Apache Spark. Spark is an open source toolset for cluster computing. While we will not be using a cluster, the typical usage for Spark is a larger set of machines or cluster that operate in parallel to analyze a big data set. An installation guide is available at https://www.dataquest.io/blog/pyspark-installation-guide. In particular, you will need to add two settings to your bash profile: SPARK_HOME and PYSPARK_SUBMIT_ARGS. SPARK_HOME is the directory where the software is installed. PYSPARK_SUBMIT_ARGS sets the number of cores to use in the local cluster.

Mac installation

To install, we download the latest TGZ file from the Spark download page at https://spark.apache.org/downloads.html, unpack the TGZ file, and move the unpacked directory to our Applications folder.

Spark relies on Scala's availability. We installed Scala in Chapter 7Sharing and Converting Jupyter Notebooks.

Open a command-line window to the Spark directory and run this...

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