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 the top transfer airports


An extension of understanding vertex degrees for airports is to determine the top transfer airports. Many airports are used as transfer points instead of being the final destination. An easy way to calculate this is by calculating the ratio of inDegrees (the number of flights to the airport) and / outDegrees (the number of flights leaving the airport). Values close to 1 may indicate many transfers, whereas values <1 indicate many outgoing flights and values >1 indicate many incoming flights.

Note that this is a simple calculation that does not consider timing or scheduling of flights, just the overall aggregate number within the dataset:

# Calculate the inDeg (flights into the airport) and 
# outDeg (flights leaving the airport)
inDeg = tripGraph.inDegrees
outDeg = tripGraph.outDegrees

# Calculate the degreeRatio (inDeg/outDeg)
degreeRatio = inDeg.join(outDeg, inDeg.id == outDeg.id) \
  .drop(outDeg.id) \
  .selectExpr("id", "double(inDegree)/double...