Book Image

Learning PySpark

By : Tomasz Drabas, Denny Lee
Book Image

Learning PySpark

By: Tomasz Drabas, Denny Lee

Overview of this book

Apache Spark is an open source framework for efficient cluster computing with a strong interface for data parallelism and fault tolerance. This book will show you how to leverage the power of Python and put it to use in the Spark ecosystem. You will start by getting a firm understanding of the Spark 2.0 architecture and how to set up a Python environment for Spark. You will get familiar with the modules available in PySpark. You will learn how to abstract data with RDDs and DataFrames and understand the streaming capabilities of PySpark. Also, you will get a thorough overview of machine learning capabilities of PySpark using ML and MLlib, graph processing using GraphFrames, and polyglot persistence using Blaze. Finally, you will learn how to deploy your applications to the cloud using the spark-submit command. By the end of this book, you will have established a firm understanding of the Spark Python API and how it can be used to build data-intensive applications.
Table of Contents (20 chapters)
Learning PySpark
Credits
Foreword
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
Index

Getting familiar with your data


Although we would strongly discourage such behavior, you can build a model without knowing your data; it will most likely take you longer, and the quality of the resulting model might be less than optimal, but it is doable.

Note

In this section, we will use the dataset we downloaded from http://packages.revolutionanalytics.com/datasets/ccFraud.csv. We did not alter the dataset itself, but it was GZipped and uploaded to http://tomdrabas.com/data/LearningPySpark/ccFraud.csv.gz. Please download the file first and save it in the same folder that contains your notebook for this chapter.

The head of the dataset looks as follows:

Thus, any serious data scientist or data modeler will become acquainted with the dataset before starting any modeling. As a first thing, we normally start with some descriptive statistics to get a feeling for what we are dealing with.

Descriptive statistics

Descriptive statistics, in the simplest sense, will tell you the basic information about...