Chapter 01: Installing Pyspark and Settingup Your Development Environment

[ 2 ]

[ 3 ]

[ 4 ]

Chapter 02: Getting Your Big Data into theSpark Environment Using RDDs

[ 5 ]

Chapter 03: Big Data Cleaning andWrangling with Spark Notebooks

[ 6 ]

[ 7 ]

[ 8 ]

Chapter 04: Aggregating and SummarizingData into Useful Reports

[ 9 ]

Chapter 05: Powerful Exploratory DataAnalysis with MLlib

[ 10 ]

Chapter 08: Immutable Design

[ 11 ]

Chapter 09: Avoiding Shuffle and ReducingOperational Expenses

[ 12 ]

[ 13 ]

Chapter 10: Saving Data in the CorrectFormat

[ 14 ]

[ 15 ]

Chapter 11: Working with the SparkKey/Value API

[ 16 ]

[ 17 ]

Chapter 12: Testing Apache Spark Jobs

[ 18 ]

[ 19 ]

Chapter 13: Leveraging the Spark GraphXAPI

[ 20 ]

[ 21 ]

[ 22 ]