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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.

Bu egzersiz

Introduction to Spark SQL in Python

kursunun bir parçasıdır
Kursu Görüntüle

Egzersiz talimatları

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

Uygulamalı interaktif egzersiz

Bu örnek kodu tamamlayarak bu egzersizi bitirin.

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