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Table of Contents
What is GROUP BY?
What are the commonly used aggregate functions?
How to use GROUP BY Multi-fields?
Filter grouping results using HAVING
Home Database Mysql Tutorial Grouping Data with GROUP BY and Aggregate Functions in MySQL

Grouping Data with GROUP BY and Aggregate Functions in MySQL

Jul 08, 2025 am 02:52 AM

To extract summary information from the database, use GROUP BY and aggregate functions. GROUP BY can group data by field, and is often used in combination with aggregate functions such as SUM, COUNT, AVG, MAX, MIN, etc.; non-aggregated fields must appear in GROUP BY after SELECT; multi-field grouping is grouped in order; HAVING is used to filter grouping results, such as filtering users with a total order amount of more than 1,000.

Grouping Data with GROUP BY and Aggregate Functions in MySQL

When you want to extract some kind of "summarized information" from the database, such as counting the average salary of each department, checking the order quantity per user, etc., you need to use GROUP BY and aggregation functions. They are two of the most core tools in MySQL that handle group statistics.

Grouping Data with GROUP BY and Aggregate Functions in MySQL

What is GROUP BY?

The function of GROUP BY is to group data by one or more fields. It is usually used with aggregate functions to perform statistical analysis of each set of data.

Grouping Data with GROUP BY and Aggregate Functions in MySQL

For example: Suppose you have an order table orders with user_id and order_amount fields. If you want to know how much order amount each user places in total, you can write it like this:

 SELECT user_id, SUM(order_amount) AS total_amount
FROM orders
GROUP BY user_id;

The above SQL means: group according to user_id , and then calculate the sum of order amounts of each group.

Grouping Data with GROUP BY and Aggregate Functions in MySQL

Note: If the fields that appear after SELECT are not the result of the aggregate function, they must appear in GROUP BY clause. Otherwise, MySQL will report an error or return unpredictable data.


What are the commonly used aggregate functions?

MySQL provides some commonly used aggregate functions for statistical analysis of grouped data. Common ones include:

  • SUM() : Sum
  • COUNT() : Count
  • AVG() : Average
  • MAX() : Maximum value
  • MIN() : Minimum value

For example, if you want to count how many employees there are in each department, you can write this:

 SELECT department_id, COUNT(*) AS employee_count
FROM employees
GROUP BY department_id;

COUNT(*) is used here to count the number of records in each group.

Sometimes you may just want to count the number of non-null values, you can use COUNT(column_name) , for example:

 SELECT department_id, COUNT(manager_id) AS has_manager_count
FROM employees
GROUP BY department_id;

This query ignores the case where manager_id is NULL.


How to use GROUP BY Multi-fields?

Sometimes you want to group by multiple fields. For example, if you want to count sales in each region every month, you need to group them by month and region at the same time:

 SELECT region, order_month, SUM(amount) AS total_sales
FROM sales_data
GROUP BY region, order_month;

In this case, MySQL will first group by region , and then subdivide by order_month within each group.

Tips: When grouping multiple fields, the order has an impact. Although the final result may be the same, the internal processing logic is different. It is recommended to arrange the field order reasonably according to business needs.


Filter grouping results using HAVING

Sometimes you just want to keep certain groupings that meet the criteria. At this time, WHERE cannot be used because WHERE filters data before grouping, and what we want is conditional filtering after grouping.

At this time, you need to use HAVING :

 SELECT user_id, SUM(order_amount) AS total_amount
FROM orders
GROUP BY user_id
HAVING total_amount > 1000;

In the example above, we only retain users with a total order amount of more than 1000.

Note: Alias ??can be used directly after HAVING (such as total_amount ), but some database versions may not support it. For compatibility, expressions can also be written directly:

 HAVING SUM(order_amount) > 1000;

Basically that's it. By mastering the combination of GROUP BY and aggregate functions, you can already handle most of the data summary needs. Although it seems simple, in actual applications, the combination method is flexible and changeable, and errors will occur if you are not careful, especially when multi-field grouping and conditional filtering.

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