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Frank Kane's Taming Big Data with Apache Spark and Python

You're reading from   Frank Kane's Taming Big Data with Apache Spark and Python Real-world examples to help you analyze large datasets with Apache Spark

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Product type Paperback
Published in Jun 2017
Publisher Packt
ISBN-13 9781787287945
Length 296 pages
Edition 1st Edition
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Author (1):
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Frank Kane Frank Kane
Author Profile Icon Frank Kane
Frank Kane
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Table of Contents (8) Chapters Close

Preface 1. Getting Started with Spark 2. Spark Basics and Spark Examples FREE CHAPTER 3. Advanced Examples of Spark Programs 4. Running Spark on a Cluster 5. SparkSQL, DataFrames, and DataSets 6. Other Spark Technologies and Libraries 7. Where to Go From Here? – Learning More About Spark and Data Science

Running the minimum temperature example and modifying it for maximums


Let's see this filter in action and find out the minimum temperature observed for each weather station in the year 1800. Go to the download package for this book and download two things: the min-temperatures Python script and the 1800.csv data file, which contains our weather information. Go ahead and download these now. When you're done, place them into your C:SparkCourse folder or wherever you're storing all the stuff for this course:

When you're ready, go ahead and double-click on min-temperatures.py and open that up in your editor. I think it makes a little bit more sense once you see this all together. Feel free to take some time to wrap your head around it and figure out what's going on here and then I'll walk you through it.

Examining the min-temperatures script

We start off with the usual boilerplate stuff, importing what we need from pyspark and setting up a SparkContext object that we're going to call MinTemperatures...

You have been reading a chapter from
Frank Kane's Taming Big Data with Apache Spark and Python
Published in: Jun 2017
Publisher: Packt
ISBN-13: 9781787287945
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