Percent of total with window functions in SQL - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is a window function in SQL?

A window function performs a calculation across a set of table rows related to the current row without collapsing the rows into a single output row.

beginner

How do you calculate the percent of total using window functions?

Divide the value of each row by the sum of all values over the entire set using SUM() as a window function, then multiply by 100.

beginner

What does the OVER() clause do in a window function?

It defines the window or set of rows the function should operate on, such as all rows or a partition of rows.

intermediate

Write a simple SQL snippet to calculate the percent of total sales per product.

SELECT product, sales, 100.0 * sales / SUM(sales) OVER() AS percent_of_total FROM sales_table;

intermediate

Why use window functions instead of GROUP BY for percent of total?

Window functions keep all rows visible and add the percent calculation as a new column, while GROUP BY aggregates rows and reduces detail.

Which SQL clause is used to define the set of rows for a window function?

A OVER()

B GROUP BY

C WHERE

D HAVING

The OVER() clause specifies the window or set of rows for the window function.

To calculate percent of total sales per row, which function is typically used inside OVER()?

A COUNT()

B MAX()

C AVG()

D SUM()

SUM() is used to get the total sales over all rows to calculate the percent of total.

What does multiplying by 100 do in a percent of total calculation?

A Converts fraction to percentage

B Rounds the number

C Filters rows

D Aggregates data

Multiplying by 100 converts the fraction to a percentage value.

Which of these is true about window functions?

A They only work with GROUP BY

B They collapse rows into one

C They add calculations without collapsing rows

D They filter rows

Window functions add calculations as new columns without collapsing rows.

If you want percent of total sales per category, what should you add to the window function?

A GROUP BY category

B PARTITION BY category

C ORDER BY category

D WHERE category

PARTITION BY divides the data into groups (categories) for the window function.

Explain how to calculate the percent of total for each row using SQL window functions.

Think about how to get total sum without grouping rows.

Describe the difference between using GROUP BY and window functions for percent of total calculations.

Consider what happens to rows in each case.

Practice

1. What does the SQL window function SUM(column) OVER () compute in a query?

easy

A. The maximum value of the column

B. The total sum of the column across all rows without grouping

C. The average of the column values

D. The sum of the column for each group defined by GROUP BY

Solution

1. Step 1: Understand window function syntax

   The syntax SUM(column) OVER () means sum over all rows without partitioning or grouping.

2. Step 2: Compare with GROUP BY sum

   Unlike GROUP BY, this sums the entire column across all rows, returning the same total for each row.

3. Final Answer:

   The total sum of the column across all rows without grouping -> Option B

4. Quick Check:

   SUM() OVER () = total sum [OK]

Hint: SUM() OVER () gives total sum for all rows, no grouping [OK]

Common Mistakes:

• Confusing window sum with GROUP BY sum
• Thinking it calculates average
• Assuming it returns max value

2. Which of the following SQL queries correctly calculates the percent of total sales per product using window functions?

easy

A. SELECT product, sales, (sales / SUM(sales) OVER ()) * 100 AS percent_total FROM sales_table;

B. SELECT product, sales, (SUM(sales) OVER () / sales) * 100 AS percent_total FROM sales_table;

C. SELECT product, sales, (sales / SUM(sales)) * 100 AS percent_total FROM sales_table GROUP BY product;

D. SELECT product, sales, (sales / COUNT(*) OVER ()) * 100 AS percent_total FROM sales_table;

Solution

1. Step 1: Identify correct window function usage

   SELECT product, sales, (sales / SUM(sales) OVER ()) * 100 AS percent_total FROM sales_table; uses SUM(sales) OVER () to get total sales across all rows, then divides each sales value by this total.

2. Step 2: Check other options for errors

   SELECT product, sales, (SUM(sales) OVER () / sales) * 100 AS percent_total FROM sales_table; divides total by sales (wrong direction). SELECT product, sales, (sales / SUM(sales)) * 100 AS percent_total FROM sales_table GROUP BY product; uses SUM(sales) without OVER(), which requires GROUP BY and won't work as intended. SELECT product, sales, (sales / COUNT(*) OVER ()) * 100 AS percent_total FROM sales_table; divides sales by count of rows, not sum.

3. Final Answer:

   SELECT product, sales, (sales / SUM(sales) OVER ()) * 100 AS percent_total FROM sales_table; -> Option A

4. Quick Check:

   Percent = sales / total sales * 100 [OK]

Hint: Divide sales by SUM() OVER () and multiply by 100 [OK]

Common Mistakes:

• Reversing numerator and denominator
• Using SUM() without OVER() in window context
• Using COUNT() instead of SUM() for total

3. Given the table sales_data with columns product and amount, what is the output of this query?

SELECT product, amount, ROUND((amount / SUM(amount) OVER ()) * 100, 1) AS percent_total FROM sales_data ORDER BY product;

Assume the data:
product | amount
-------|-------
A | 50
B | 30
C | 20

medium

A. [{"product": "A", "amount": 50, "percent_total": 100.0}, {"product": "B", "amount": 30, "percent_total": 100.0}, {"product": "C", "amount": 20, "percent_total": 100.0}]

B. [{"product": "A", "amount": 50, "percent_total": 33.3}, {"product": "B", "amount": 30, "percent_total": 20.0}, {"product": "C", "amount": 20, "percent_total": 13.3}]

C. [{"product": "A", "amount": 50, "percent_total": 25.0}, {"product": "B", "amount": 30, "percent_total": 15.0}, {"product": "C", "amount": 20, "percent_total": 10.0}]

D. [{"product": "A", "amount": 50, "percent_total": 50.0}, {"product": "B", "amount": 30, "percent_total": 30.0}, {"product": "C", "amount": 20, "percent_total": 20.0}]

Solution

1. Step 1: Calculate total amount

   Total = 50 + 30 + 20 = 100.

2. Step 2: Calculate percent for each product

   Percent = (amount / total) * 100 rounded to 1 decimal:
   A: (50/100)*100 = 50.0
   B: (30/100)*100 = 30.0
   C: (20/100)*100 = 20.0

3. Final Answer:

   [{"product": "A", "amount": 50, "percent_total": 50.0}, {"product": "B", "amount": 30, "percent_total": 30.0}, {"product": "C", "amount": 20, "percent_total": 20.0}] -> Option D

4. Quick Check:

   Percent totals sum to 100% [OK]

Hint: Sum amounts, divide each by total, multiply by 100 [OK]

Common Mistakes:

• Not rounding results
• Using COUNT() instead of SUM()
• Calculating percent incorrectly (e.g., reversed division)

4. You wrote this query to calculate percent of total sales:

SELECT product, sales, (sales / SUM(sales)) * 100 AS percent_total FROM sales_table;

But it gives an error. What is the problem?

medium

A. SUM(sales) requires a GROUP BY clause or window function syntax

B. sales column does not exist

C. Multiplying by 100 is invalid syntax

D. Missing WHERE clause

Solution

1. Step 1: Analyze use of SUM() without OVER()

   SUM(sales) without GROUP BY or window function context causes error because SQL doesn't know how to aggregate without grouping.

2. Step 2: Correct usage

   Use either GROUP BY product with SUM(sales) or use window function SUM(sales) OVER () to get total sum without grouping.

3. Final Answer:

   SUM(sales) requires a GROUP BY clause or window function syntax -> Option A

4. Quick Check:

   SUM() needs GROUP BY or OVER() [OK]

Hint: Use SUM() OVER () or GROUP BY with SUM() [OK]

Common Mistakes:

• Ignoring need for GROUP BY with aggregate functions
• Assuming multiplication by 100 causes error
• Thinking WHERE clause is mandatory here

5. You have a table orders with columns category and amount. Write a query to show each category, total amount per category, and percent of total amount across all categories. Which query is correct?

hard

A. SELECT category, SUM(amount) AS category_total, (SUM(amount) / COUNT(*) OVER ()) * 100 AS percent_total FROM orders GROUP BY category;

B. SELECT category, amount, (amount / SUM(amount) OVER ()) * 100 AS percent_total FROM orders ORDER BY category;

C. SELECT category, SUM(amount) AS category_total, (SUM(amount) / SUM(SUM(amount)) OVER ()) * 100 AS percent_total FROM orders GROUP BY category ORDER BY category;

D. SELECT category, SUM(amount) AS category_total, (SUM(amount) / SUM(amount)) * 100 AS percent_total FROM orders GROUP BY category;

Solution

1. Step 1: Calculate total per category

   Use SUM(amount) GROUP BY category to get total per category.

2. Step 2: Calculate percent of total across all categories

   Use window function SUM(SUM(amount)) OVER () to get grand total across all categories, then divide category total by this and multiply by 100.

3. Step 3: Verify query correctness

   SELECT category, SUM(amount) AS category_total, (SUM(amount) / SUM(SUM(amount)) OVER ()) * 100 AS percent_total FROM orders GROUP BY category ORDER BY category; correctly combines GROUP BY with window function for total sum. SELECT category, amount, (amount / SUM(amount) OVER ()) * 100 AS percent_total FROM orders ORDER BY category; uses amount per row, not category total. SELECT category, SUM(amount) AS category_total, (SUM(amount) / COUNT(*) OVER ()) * 100 AS percent_total FROM orders GROUP BY category; incorrectly uses COUNT() for total. SELECT category, SUM(amount) AS category_total, (SUM(amount) / SUM(amount)) * 100 AS percent_total FROM orders GROUP BY category; divides sum by itself, always 100%.

4. Final Answer:

   SELECT category, SUM(amount) AS category_total, (SUM(amount) / SUM(SUM(amount)) OVER ()) * 100 AS percent_total FROM orders GROUP BY category ORDER BY category; -> Option C

5. Quick Check:

   Percent = category sum / total sum * 100 [OK]

Hint: Use GROUP BY with SUM() and window SUM(SUM(amount)) OVER () for total [OK]

Common Mistakes:

• Using row amount instead of category sum
• Using COUNT() instead of SUM() for total
• Dividing sum by itself always gives 100%