Databricks Data Engineer Associate Question 120
Single answerA data engineer is analyzing a dataset in a Databricks notebook. The dataset contains a column named sales_amount. The column has some NULL values, and the engineer wants to count the total number of rows in the column, including rows with NULL values. Which of the following methods will correctly achieve this?
- A
Use the COUNT(sales_amount) function
- B
Use the COUNT(*) function
- C
Use the COUNT(1) function
- D
Use the SUM(CASE WHEN sales_amount IS NOT NULL THEN 1 ELSE 0 END) function
Show answer and explanation
Correct answer: B
Explanation
The COUNT() function counts all rows in a dataset, including those with NULL values in specific columns. Other variants like COUNT(column_name) or conditional expressions explicitly exclude NULL values, which is not desired in this case. Therefore, COUNT() is the correct choice for counting all rows, including NULLs.
- A. Incorrect.
COUNT(sales_amount) only counts rows where the
sales_amountcolumn is not NULL. It skips NULL values and will not give the total row count. - B. Correct.
COUNT(*) counts all rows in the dataset, including rows where the
sales_amountcolumn is NULL. This is the correct option. - C. Incorrect.
COUNT(1) behaves like COUNT(*), but it is not specific to counting rows with NULL values in a particular column, so it is not relevant to this scenario.
- D. Incorrect.
SUM(CASE WHEN sales_amount IS NOT NULL THEN 1 ELSE 0 END) explicitly excludes NULL values by design and only counts rows where
sales_amountis not NULL. This is not the correct method to count all rows.