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PySpark Recipes

A Problem-Solution Approach with PySpark2

  • Raju Kumar Mishra

Table of contents

  1. Front Matter
    Pages i-xxiii
  2. Raju Kumar Mishra
    Pages 15-44
  3. Raju Kumar Mishra
    Pages 45-83
  4. Raju Kumar Mishra
    Pages 115-136
  5. Raju Kumar Mishra
    Pages 137-161
  6. Raju Kumar Mishra
    Pages 163-185
  7. Raju Kumar Mishra
    Pages 187-233
  8. Raju Kumar Mishra
    Pages 235-259
  9. Back Matter
    Pages 261-265

About this book

Introduction

Quickly find solutions to common programming problems encountered while processing big data. Content is presented in the popular problem-solution format. Look up the programming problem that you want to solve. Read the solution. Apply the solution directly in your own code. Problem solved!

PySpark Recipes covers Hadoop and its shortcomings. The architecture of Spark, PySpark, and RDD are presented. You will learn to apply RDD to solve day-to-day big data problems. Python and NumPy are included and make it easy for new learners of PySpark to understand and adopt the model.

What You Will Learn:  
  • Understand the advanced features of PySpark and SparkSQL
  • Optimize your code
  • Program SparkSQL with Python
  • Use Spark Streaming and Spark MLlib with Python
  • Perform graph analysis with GraphFrames

Keywords

Big Data Spark Python Numpy Scipy Resilient Distributed Database Advanced PySpark Spark SQL MLLIb PySpark2

Authors and affiliations

  • Raju Kumar Mishra
    • 1
  1. 1.BangaloreIndia

Bibliographic information

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