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PySpark Cookbook

You're reading from   PySpark Cookbook Over 60 recipes for implementing big data processing and analytics using Apache Spark and Python

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Product type Paperback
Published in Jun 2018
Publisher Packt
ISBN-13 9781788835367
Length 330 pages
Edition 1st Edition
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Authors (2):
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Tomasz Drabas Tomasz Drabas
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Tomasz Drabas
Denny Lee Denny Lee
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Denny Lee
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Toc

Table of Contents (9) Chapters Close

Preface 1. Installing and Configuring Spark FREE CHAPTER 2. Abstracting Data with RDDs 3. Abstracting Data with DataFrames 4. Preparing Data for Modeling 5. Machine Learning with MLlib 6. Machine Learning with the ML Module 7. Structured Streaming with PySpark 8. GraphFrames – Graph Theory with PySpark

Installing and Configuring Spark

In this chapter, we will cover how to install and configure Spark, either as a local instance, a multi-node cluster, or in a virtual environment. You will learn the following recipes:

  • Installing Spark requirements
  • Installing Spark from sources
  • Installing Spark from binaries
  • Configuring a local instance of Spark
  • Configuring a multi-node instance of Spark
  • Installing Jupyter
  • Configuring a session in Jupyter
  • Working with Cloudera Spark images
You have been reading a chapter from
PySpark Cookbook
Published in: Jun 2018
Publisher: Packt
ISBN-13: 9781788835367
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