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Impara Challenge: Analyzing Sales Data with Spark SQL | Section
Data Processing with PySpark
Sezione 1. Capitolo 9
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Challenge: Analyzing Sales Data with Spark SQL

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You are given a flights dataset as a list of rows. Load it into a DataFrame, register it as a temporary view, and answer the following using spark.sql(). Store results in the specified variables:

  1. Find the top 3 routes (unique AirportFrom + AirportTo pairs) by average Length – store as a list of tuples [(origin, destination, avg_length), ...] in top_routes_by_length;
  2. For each airline, find the flight with the longest Length using a window function with row_number() – store as a DataFrame in longest_flight_per_airline with columns Airline, Flight, Length;
  3. Count how many delayed flights (Delay == 1) per DayOfWeek – store as a list of tuples [(day_of_week, count), ...] sorted by DayOfWeek ascending in delays_by_dow.

Print all results.

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Sezione 1. Capitolo 9
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