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

Determining airport ranking using PageRank


Because GraphFrames is built on top of GraphX, there are several algorithms that we can immediately leverage. PageRank was popularized by the Google Search Engine and created by Larry Page. To quote Wikipedia:

"PageRank works by counting the number and quality of links to a page to determine a rough estimate of how important the website is. The underlying assumption is that more important websites are likely to receive more links from other websites."

While the preceding example refers to web pages, this concept readily applies to any graph structure whether it is created from web pages, bike stations, or airports. Yet the interface via GraphFrames is as simple as calling a method. GraphFrames.PageRank will return the PageRank results as a new column appended to the vertices DataFrame to simplify our downstream analysis.

As there are many flights and connections through the various airports included in this dataset, we can use the PageRank algorithm...