# Group By

# GROUP BY using HAVING

SELECT department, COUNT(*) AS "Man_Power"
FROM employees
GROUP BY department
HAVING COUNT(*) >= 10;

Using GROUP BY ... HAVING to filter aggregate records is analogous to using SELECT ... WHERE to filter individual records.

You could also say HAVING Man_Power >= 10 since HAVING understands "aliases".

# Group By using Group Concat

Group Concat is used in MySQL to get concatenated values of expressions with more than one result per column. Meaning, there are many rows to be selected back for one column such as Name(1):Score(*)

Name Score
Adam A+
Adam A-
Adam B
Adam C+
Bill D-
John A-
SELECT Name, GROUP_CONCAT(Score ORDER BY Score desc SEPERATOR ' ') AS Grades
FROM   Grade
GROUP BY Name

Results:

+------+------------+ 
| Name | Grades     | 
+------+------------+ 
| Adam | C+ B A- A+ | 
| Bill | D-         | 
| John | A-         | 
+------+------------+ 

# Group By Using MIN function

Assume a table of employees in which each row is an employee who has a name, a department, and a salary.

SELECT department, MIN(salary) AS "Lowest salary"
FROM employees
GROUP BY department;

This would tell you which department contains the employee with the lowest salary, and what that salary is. Finding the name of the employee with the lowest salary in each department is a different problem, beyond the scope of this Example. See "groupwise max".

# GROUP BY with AGGREGATE functions

Table ORDERS

+---------+------------+----------+-------+--------+
| orderid | customerid | customer | total | items  |
+---------+------------+----------+-------+--------+
|       1 |          1 | Bob      |  1300 |     10 |
|       2 |          3 | Fred     |   500 |      2 |
|       3 |          5 | Tess     |  2500 |      8 |
|       4 |          1 | Bob      |   300 |      6 |
|       5 |          2 | Carly    |   800 |      3 |
|       6 |          2 | Carly    |  1000 |     12 |
|       7 |          3 | Fred     |   100 |      1 |
|       8 |          5 | Tess     | 11500 |     50 |
|       9 |          4 | Jenny    |   200 |      2 |
|      10 |          1 | Bob      |   500 |     15 |
+---------+------------+----------+-------+--------+

  • COUNT

Return the number of rows that satisfy a specific criteria in WHERE clause.

E.g.: Number of orders for each customer.

SELECT customer, COUNT(*) as orders
FROM orders
GROUP BY customer
ORDER BY customer

Result:

+----------+--------+
| customer | orders |
+----------+--------+
| Bob      |      3 |
| Carly    |      2 |
| Fred     |      2 |
| Jenny    |      1 |
| Tess     |      2 |
+----------+--------+

  • SUM

Return the sum of the selected column.

E.g.: Sum of the total and items for each customer.

SELECT customer, SUM(total) as sum_total, SUM(items) as sum_items
FROM orders
GROUP BY customer
ORDER BY customer

Result:

+----------+-----------+-----------+
| customer | sum_total | sum_items |
+----------+-----------+-----------+
| Bob      |      2100 |        31 |
| Carly    |      1800 |        15 |
| Fred     |       600 |         3 |
| Jenny    |       200 |         2 |
| Tess     |     14000 |        58 |
+----------+-----------+-----------+

  • AVG

Return the average value of a column of numeric value.

E.g.: Average order value for each customers.

SELECT customer, AVG(total) as avg_total
FROM orders
GROUP BY customer
ORDER BY customer

Result:

+----------+-----------+
| customer | avg_total |
+----------+-----------+
| Bob      |       700 |
| Carly    |       900 |
| Fred     |       300 |
| Jenny    |       200 |
| Tess     |      7000 |
+----------+-----------+

  • MAX

Return the highest value of a certain column or expression.

E.g.: Highest order total for each customers.

SELECT customer, MAX(total) as max_total
FROM orders
GROUP BY customer
ORDER BY customer

Result:

+----------+-----------+
| customer | max_total |
+----------+-----------+
| Bob      |      1300 |
| Carly    |      1000 |
| Fred     |       500 |
| Jenny    |       200 |
| Tess     |     11500 |
+----------+-----------+

  • MIN

Return the lowest value of a certain column or expression.

E.g.: Lowest order total for each customers.

SELECT customer, MIN(total) as min_total
FROM orders
GROUP BY customer
ORDER BY customer

Result:

+----------+-----------+
| customer | min_total |
+----------+-----------+
| Bob      |       300 |
| Carly    |       800 |
| Fred     |       100 |
| Jenny    |       200 |
| Tess     |      2500 |
+----------+-----------+

# GROUP BY USING SUM Function

SELECT product, SUM(quantity) AS "Total quantity"
FROM order_details
GROUP BY product;

# GROUP BY USING COUNT Function

SELECT department, COUNT(*) AS "Man_Power"
FROM employees
GROUP BY department;

# Syntax

  1. SELECT expression1, expression2, ... expression_n,
  2. aggregate_function (expression)
  3. FROM tables
  4. [WHERE conditions]
  5. GROUP BY expression1, expression2, ... expression_n;

# Parameters

Parameter DETAILS
expression1, expression2, ... expression_n The expressions that are not encapsulated within an aggregate function and must be included in the GROUP BY clause.
aggregate_function A function such as SUM, COUNT, MIN, MAX, or AVG functions.
tables he tables that you wish to retrieve records from. There must be at least one table listed in the FROM clause.
WHERE conditions Optional. The conditions that must be met for the records to be selected.

# Remarks

The MySQL GROUP BY clause is used in a SELECT statement to collect data across multiple records and group the results by one or more columns.

Its behavior is governed in part by the value of the ONLY_FULL_GROUP_BY variable. When this is enabled, SELECT statements that group by any column not in the output return an error. (This is the default as of 5.7.5.) Both setting and not setting this variable can cause problems for naive users or users accustomed to other DBMSs.