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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

Abstracting Data with DataFrames

In this chapter, you will learn about the following recipes:

  • Creating DataFrames
  • Accessing underlying RDDs
  • Performance optimizations
  • Inferring the schema using reflection
  • Specifying the schema programmatically
  • Creating a temporary table
  • Using SQL to interact with DataFrames
  • Overview of DataFrame transformations
  • Overview of DataFrame actions
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