Apache Spark 3 for Data Engineering and Analytics with Python - Distinct Drop Duplicates Order By

The video tutorial demonstrates how to work with dataframes using SQL functions in PySpark. It covers obtaining unique rows with the distinct function, dropping duplicates based on specific columns, and ordering data by year in descending order. The tutorial provides step-by-step instructions and examples to help learners understand these data manipulation techniques.

What is the primary purpose of using the distinct function in a dataset?

• To remove duplicate rows and get unique records

• To calculate the sum of a column

• To filter rows based on a condition

• To sort the data in ascending order

Which SQL function is used to remove duplicate records from a DataFrame?

• dropDuplicates

• filter

• orderBy

• groupBy

In the context of the tutorial, what does the alias function do?

• It renames a column in the DataFrame

• It sorts the data in descending order

• It filters rows based on a condition

• It calculates the average of a column

When dropping duplicates, which columns were used in the example to identify duplicates?

• Email and phone number

• First name and last name

• Year and active indicator

• Date of birth and address

What is the result of ordering a DataFrame by year in descending order?

• The data is grouped by year

• The latest years appear first

• The earliest years appear first

• The data is filtered by year

Which function is used to order data in a DataFrame?

• filter

• groupBy

• select

• orderBy

What is the effect of setting the ascending property to false when ordering data?

• Data is grouped by a column

• Data is filtered by a condition

• Data is ordered in descending order

• Data is ordered in ascending order