PySpark Recipes: A Problem-Solution Approach with PySpark2

PySpark Recipes: A Problem-Solution Approach with PySpark2 Front Cover
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265 pages

Book Description

Quickly find solutions to common problems encountered while 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 . Problem solved!

PySpark Recipes covers Hadoop and its shortcomings. The of Spark, PySpark, and RDD are presented. You will learn to apply RDD to solve day-to-day big data problems. 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 PySpark2 and SparkSQL
  • Optimize your code
  • Program SparkSQL with Python
  • Use Spark Streaming and Spark MLlib with Python
  • Perform graph with GraphFrames

Who This Book Is For 

Data analysts, Python programmers, big data enthusiasts

Table of Contents

Chapter 1: The Era of Big Data, Hadoop, and Other Big Data Processing Frameworks
Chapter 2: Installation
Chapter 3: Introduction to Python and NumPy
Chapter 4: Spark Architecture and the Resilient Distributed Dataset
Chapter 5: The Power of Pairs: Paired RDDs
Chapter 6: I/O in PySpark
Chapter 7: Optimizing PySpark and PySpark Streaming
Chapter 8: PySparkSQL
Chapter 9: PySpark MLlib and Linear Regression

Book Details

  • Title: PySpark Recipes: A Problem-Solution Approach with PySpark2
  • Author:
  • Length: 265 pages
  • Edition: 1st ed.
  • Language: English
  • Publisher:
  • Publication Date: 2018-01-10
  • ISBN-10: 1484231406
  • ISBN-13: 9781484231401
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UsersCloud Click to downloadTrue PDF, EPUB3.312/10/2017
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