GROUP BY with multiple columns in MySQL

Introduction

Grouping data by multiple columns helps you organize and summarize information based on more than one category at the same time.

You want to count how many sales happened for each product in each store.

You need to find the total hours worked by each employee in each department.

You want to see the average score of students grouped by both class and subject.

You want to summarize expenses by both month and category.

Syntax

MySQL

SELECT column1, column2, aggregate_function(column3)
FROM table_name
GROUP BY column1, column2;

You list all the columns you want to group by after GROUP BY, separated by commas.

Aggregate functions like COUNT(), SUM(), AVG() work on other columns to summarize data.

Examples

Counts how many employees are in each role within each department.

MySQL

SELECT department, role, COUNT(*)
FROM employees
GROUP BY department, role;

Adds up total sales for each product in each city.

MySQL

SELECT city, product, SUM(sales)
FROM sales_data
GROUP BY city, product;

Finds average temperature for each month of each year.

MySQL

SELECT year, month, AVG(temperature)
FROM weather
GROUP BY year, month;

Sample Program

This query groups orders by customer and product category, counting orders and summing amounts spent.

MySQL

CREATE TABLE orders (
  order_id INT,
  customer_id INT,
  product_category VARCHAR(50),
  order_amount DECIMAL(10,2)
);

INSERT INTO orders VALUES
(1, 101, 'Books', 15.99),
(2, 102, 'Books', 25.50),
(3, 101, 'Electronics', 199.99),
(4, 103, 'Books', 8.99),
(5, 102, 'Electronics', 99.99),
(6, 101, 'Books', 12.00);

SELECT customer_id, product_category, COUNT(*) AS order_count, SUM(order_amount) AS total_spent
FROM orders
GROUP BY customer_id, product_category
ORDER BY customer_id, product_category;

Important Notes

When using GROUP BY with multiple columns, the result groups rows that have the same values in all those columns.

Always include all non-aggregated columns in the GROUP BY clause to avoid errors.

Ordering results after grouping helps read the summary data more easily.

Summary

GROUP BY with multiple columns groups data by all listed columns together.

Use aggregate functions to summarize data within each group.

This helps analyze data across multiple categories at once.

Practice

1. What does the GROUP BY clause with multiple columns do in a MySQL query?

easy

A. It groups rows based on only the first column listed.

B. It groups rows based on the combination of values in all specified columns.

C. It sorts the rows without grouping them.

D. It filters rows that have duplicate values in any column.

Solution

1. Step 1: Understand GROUP BY behavior

   The GROUP BY clause groups rows that have the same values in the specified columns together.

2. Step 2: Multiple columns effect

   When multiple columns are listed, grouping happens on the combined values of all those columns, not individually.

3. Final Answer:

   It groups rows based on the combination of values in all specified columns. -> Option B

4. Quick Check:

   GROUP BY multiple columns groups by combined values [OK]

Hint: GROUP BY multiple columns groups by combined column values [OK]

Common Mistakes:

• Thinking it groups by each column separately
• Confusing GROUP BY with ORDER BY
• Assuming it filters duplicates instead of grouping

2. Which of the following is the correct syntax to group data by columns city and department in MySQL?

easy

A. SELECT city, department FROM employees GROUP BY city, department;

B. SELECT city, department FROM employees GROUP city, department;

C. SELECT city, department FROM employees GROUP BY city department;

D. SELECT city, department FROM employees GROUP BY (city, department);

Solution

1. Step 1: Identify correct GROUP BY syntax

   The correct syntax uses GROUP BY followed by column names separated by commas.

2. Step 2: Check each option

   SELECT city, department FROM employees GROUP BY city, department; uses correct syntax with commas. Options A, B, and D have syntax errors or wrong keywords.

3. Final Answer:

   SELECT city, department FROM employees GROUP BY city, department; -> Option A

4. Quick Check:

   GROUP BY columns separated by commas [OK]

Hint: Use commas to separate columns in GROUP BY [OK]

Common Mistakes:

• Omitting commas between columns
• Using wrong keywords like GROUP instead of GROUP BY
• Using parentheses incorrectly around columns

3. Given the table sales with columns region, product, and amount, what will this query return?

SELECT region, product, SUM(amount) FROM sales GROUP BY region, product;

medium

A. Syntax error due to missing alias for SUM(amount).

B. Total sales amount for each region only.

C. Total sales amount for each product only.

D. Total sales amount for each region and product combination.

Solution

1. Step 1: Understand GROUP BY with multiple columns

   The query groups rows by both region and product together.

2. Step 2: Apply SUM aggregation

   Within each group, it sums the amount values, giving total sales per region-product pair.

3. Final Answer:

   Total sales amount for each region and product combination. -> Option D

4. Quick Check:

   GROUP BY multiple columns sums per combined group [OK]

Hint: GROUP BY multiple columns sums per combined group [OK]

Common Mistakes:

• Thinking it sums only by one column
• Expecting syntax error without alias (alias optional)
• Confusing GROUP BY with WHERE filtering

4. Identify the error in this query:

SELECT city, department, COUNT(*) FROM employees GROUP BY city;

medium

A. Missing department in GROUP BY causes error or incorrect grouping.

B. COUNT(*) cannot be used with GROUP BY.

C. SELECT must include only aggregated columns.

D. GROUP BY should be after WHERE clause.

Solution

1. Step 1: Check SELECT and GROUP BY columns

   The query selects city and department but groups only by city.

2. Step 2: Understand grouping rules

   All non-aggregated columns in SELECT must appear in GROUP BY to avoid errors or unpredictable results.

3. Final Answer:

   Missing department in GROUP BY causes error or incorrect grouping. -> Option A

4. Quick Check:

   All selected non-aggregated columns must be in GROUP BY [OK]

Hint: Include all non-aggregated SELECT columns in GROUP BY [OK]

Common Mistakes:

• Selecting columns not in GROUP BY without aggregation
• Thinking COUNT(*) is invalid with GROUP BY
• Misplacing GROUP BY clause

5. You have a transactions table with columns store_id, employee_id, and sales_amount. You want to find the total sales per store and employee but only for employees with total sales above 1000. Which query correctly achieves this?

hard

A. SELECT store_id, employee_id, SUM(sales_amount) FROM transactions GROUP BY store_id HAVING SUM(sales_amount) > 1000;

B. SELECT store_id, employee_id, SUM(sales_amount) FROM transactions WHERE SUM(sales_amount) > 1000 GROUP BY store_id, employee_id;

C. SELECT store_id, employee_id, SUM(sales_amount) FROM transactions GROUP BY store_id, employee_id HAVING SUM(sales_amount) > 1000;

D. SELECT store_id, employee_id, SUM(sales_amount) FROM transactions GROUP BY employee_id, store_id WHERE SUM(sales_amount) > 1000;

Solution

1. Step 1: Group by both store_id and employee_id

   We need totals per store and employee, so GROUP BY both columns together.

2. Step 2: Filter groups with HAVING clause

   Use HAVING to filter groups where total sales exceed 1000. WHERE cannot filter aggregated results.

3. Final Answer:

   SELECT store_id, employee_id, SUM(sales_amount) FROM transactions GROUP BY store_id, employee_id HAVING SUM(sales_amount) > 1000; -> Option C

4. Quick Check:

   Use HAVING to filter aggregated groups [OK]

Hint: Use HAVING to filter after GROUP BY aggregation [OK]

Common Mistakes:

• Using WHERE to filter aggregated results
• Grouping by only one column instead of both
• Placing WHERE after GROUP BY