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Aggregating the same column twice

There are cases where dot notation can be more cumbersome than SQL. This exercise calculates the first and last times for each train line. The following code does this using dot notation. 

from pyspark.sql.functions import min, max, col
expr = [min(col("time")).alias('start'), max(col("time")).alias('end')]
dot_df = df.groupBy("train_id").agg(*expr)
dot_df.show()

+--------+-----+-----+
|train_id|start|  end|
+--------+-----+-----+
|     217|6:06a|6:59a|
|     324|7:59a|9:05a|
+--------+-----+-----+

Your mission is to achieve this same result using a SQL query. The dataframe df has been registered as a table named schedule.

Cet exercice fait partie du cours

Introduction to Spark SQL in Python

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Instructions

  • Write a SQL query that gives an identical result to the dot notation query.

Exercice interactif pratique

Essayez cet exercice en complétant cet exemple de code.

# Write a SQL query giving a result identical to dot_df
query = "SELECT ____ FROM schedule ____ ____ ____"
sql_df = spark.sql(query)
sql_df.show()
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