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Learning PySpark

You're reading from   Learning PySpark Build data-intensive applications locally and deploy at scale using the combined powers of Python and Spark 2.0

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Product type Paperback
Published in Feb 2017
Publisher Packt
ISBN-13 9781786463708
Length 274 pages
Edition 1st Edition
Languages
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Authors (2):
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Denny Lee Denny Lee
Author Profile Icon Denny Lee
Denny Lee
Tomasz Drabas Tomasz Drabas
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Tomasz Drabas
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Table of Contents (13) Chapters Close

Preface 1. Understanding Spark 2. Resilient Distributed Datasets FREE CHAPTER 3. DataFrames 4. Prepare Data for Modeling 5. Introducing MLlib 6. Introducing the ML Package 7. GraphFrames 8. TensorFrames 9. Polyglot Persistence with Blaze 10. Structured Streaming 11. Packaging Spark Applications 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...
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