Running SQL Queries Programmatically

DataFrames can be easily manipulated using SQL queries in PySpark. The sql() function in a SparkSession enables applications to run SQL queries programmatically and returns the result as another DataFrame. In this exercise, you'll create a temporary table of DataFrame that you have created previously, then construct a query to select the names of the people from the temporary table and assign the result to a new DataFrame.

Remember, you already have a SparkSession spark and a DataFrame available in your workspace.

This exercise is part of the course

Big Data Fundamentals with PySpark

View Course

Exercise instructions

Create a temporary table people.
Construct a query to select the names of the people from the temporary table people.
Assign the result of Spark's query to a new DataFrame - people_df_names.
Print the top 10 names of the people from people_df_names DataFrame.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Create a temporary table "people"
people_df.____("people")

# Construct a query to select the names of the people from the temporary table "people"
query = '''SELECT name FROM ____'''

# Assign the result of Spark's query to people_df_names
people_df_names = spark.sql(____)

# Print the top 10 names of the people
people_df_names.____(____)

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