Though this book aims to explain everything from first principles, it would be advantageous (though not strictly required) to have a basic knowledge of mathematical notation and basic programming skills in a language that can be used for data transformation, such as SQL, Base SAS, R, or Python. A good website for beginners to learn about SQL and Python is https://www.w3schools.com.

It is assumed that you have access to a physical or virtual machine provisioned with the CentOS Linux 7 (or Red Hat Linux) operating system. If you do not, Chapter 2, Setting Up a Local Development Environment, describes the various options available to provision a CentOS 7 virtual machine (VM), including via cloud-computing platforms such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP), virtual private server hosting companies or free virtualization software such as Oracle VirtualBox and VMWare Workstation Player that can be installed on your local physical device, such as a desktop or laptop.

A basic knowledge of Linux shell commands is required in order to install, configure, and provision a self-contained local development environment hosting the prerequisite software services detailed in Chapter 2, Setting Up a Local Development Environment. A good website for beginners to learn about the Linux command line is http://linuxcommand.org.

You can download the example code files for this book from your account at www.packt.com. If you purchased this book elsewhere, you can visit www.packt.com/support and register to have the files emailed directly to you.

You can download the code files by following these steps:

1. Log in or register at www.packt.com.
2. Select the SUPPORT tab.
3. Click on Code Downloads & Errata.
4. Enter the name of the book in the Search box and follow the onscreen instructions.

Once the file is downloaded, please make sure that you unzip or extract the folder using the latest version of:

• WinRAR/7-Zip for Windows
• Zipeg/iZip/UnRarX for Mac
• 7-Zip/PeaZip for Linux

The code bundle for the book is also hosted on GitHub at https://github.com/PacktPublishing/Machine-Learning-with-Apache-Spark-Quick-Start-Guide. In case there's an update to the code, it will be updated on the existing GitHub repository.

We also have other code bundles from our rich catalog of books and videos available at https://github.com/PacktPublishing/. Check them out!

There are a number of text conventions used throughout this book.

CodeInText: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "Mount the downloaded WebStorm-10*.dmg disk image file as another disk in your system."

A block of code is set as follows:

import findspark
findspark.init()
from pyspark import SparkContext, SparkConf
import random

Any command-line input or output is written as follows:

> source /etc/profile.d/java.sh
> echo $PATH
> echo $JAVA_HOME

Bold: Indicates a new term, an important word, or words that you see onscreen. For example, words in menus or dialog boxes appear in the text like this. Here is an example: "Select System info from the Administration panel."