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Learning Jupyter 5

You're reading from   Learning Jupyter 5 Explore interactive computing using Python, Java, JavaScript, R, Julia, and JupyterLab

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Product type Paperback
Published in Aug 2018
Publisher
ISBN-13 9781789137408
Length 282 pages
Edition 2nd Edition
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Author (1):
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Dan Toomey Dan Toomey
Author Profile Icon Dan Toomey
Dan Toomey
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Table of Contents (14) Chapters Close

Preface 1. Introduction to Jupyter FREE CHAPTER 2. Jupyter Python Scripting 3. Jupyter R Scripting 4. Jupyter Julia Scripting 5. Jupyter Java Coding 6. Jupyter JavaScript Coding 7. Jupyter Scala 8. Jupyter and Big Data 9. Interactive Widgets 10. Sharing and Converting Jupyter Notebooks 11. Multiuser Jupyter Notebooks 12. What's Next? 13. Other Books You May Enjoy

First Spark script


Our first script reads in a text file and sees how much the line lengths add up to, as shown next. Note that we are reading in the Notebook file we are running; the Notebook is named Spark File Lengths, and is stored in the Spark File Lengths.ipynb file:

import pyspark
if not 'sc' in globals():
    sc = pyspark.SparkContext()
lines = sc.textFile("Spark File Line Lengths.ipynb")
lineLengths = lines.map(lambda s: len(s))
totalLengths = lineLengths.reduce(lambda a, b: a + b)
print(totalLengths)

 

In the print(totalLengths) script, we first initialize Spark, but only if we have not done so already. Spark will complain if you try to initialize it more than once, so all Spark scripts should have this if statement prefix.

The script reads in a text file (the source of this script), takes every line and computes its length, and then adds all the lengths together.

A lambda function is an anonymous (not named) function that takes arguments and returns a value. In the first case, given...

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