Chapter 1, Installing and Configuring Spark, shows us how to install and configure Spark, either as a local instance, as a multi-node cluster, or in a virtual environment.

Chapter 2, Abstracting Data with RDDs, covers how to work with Apache Spark Resilient Distributed Datasets (RDDs).

Chapter 3, Abstracting Data with DataFrames, explores the current fundamental data structure—DataFrames.

Chapter 4, Preparing Data for Modeling, covers how to clean up your data and prepare it for modeling.

Chapter 5, Machine Learning with MLlib, shows how to build machine learning models with PySpark's MLlib module.

Chapter 6, Machine Learning with the ML Module, moves on to the currently supported machine learning module of PySpark—the ML module.

Chapter 7, Structured Streaming with PySpark, covers how to work with Apache Spark structured streaming within PySpark.

Chapter 8, GraphFrames – Graph Theory with PySpark, shows how to work with GraphFrames for Apache Spark.