Book Image

PySpark Cookbook

By : Denny Lee, Tomasz Drabas
Book Image

PySpark Cookbook

By: Denny Lee, Tomasz Drabas

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. The PySpark Cookbook presents effective and time-saving recipes for leveraging the power of Python and putting it to use in the Spark ecosystem. You’ll start by learning the Apache Spark architecture and how to set up a Python environment for Spark. You’ll then get familiar with the modules available in PySpark and start using them effortlessly. In addition to this, you’ll discover how to abstract data with RDDs and DataFrames, and understand the streaming capabilities of PySpark. You’ll then move on to using ML and MLlib in order to solve any problems related to the machine learning capabilities of PySpark and use GraphFrames to solve graph-processing problems. Finally, you will explore how to deploy your applications to the cloud using the spark-submit command. By the end of this book, you will be able to use the Python API for Apache Spark to solve any problems associated with building data-intensive applications.
Table of Contents (13 chapters)
Title Page
Packt Upsell
Contributors
Preface
Index

Using PageRank to determine airport ranking


PageRank is an algorithm popularized by the Google Search Engine and created by Larry Page. Ian Rogers says (see http://www.cs.princeton.edu/~chazelle/courses/BIB/pagerank.htm):

"(...)PageRank is a “vote”, by all the other pages on the Web, about how important a page is. A link to a page counts as a vote of support. If there’s no link there’s no support (but it’s an abstention from voting rather than a vote against the page)."

As you might imagine, this method can be applied to other problems and not only to ranking web pages. In our context, we can use it to determine airport ranking. To achieve this, we can use the number of flights and connections to and from various airports included that are in this departure delay dataset. 

Getting ready

Ensure that you have created the graph GraphFrame from the preceding subsections.

How to do it...

Execute the following code snippet to determine the most important airport in our dataset via the PageRank algorithm...