MariaDB Avg()函数用于检索表达式的平均值。

语法：

SELECT AVG(aggregate_expression)  
FROM tables  
[WHERE conditions];

或者 -

SELECT expression1, expression2, ... expression_n,  
AVG(aggregate_expression)  
FROM tables  
[WHERE conditions]  
GROUP BY expression1, expression2, ... expression_n;

数据准备

在"testdb"数据库中创建一个"students"表，并插入一些数据。参考以下创建语句 -

USE testdb;
DROP TABLE students;
-- 创建新表
CREATE TABLE students(  
    student_id INT NOT NULL AUTO_INCREMENT,  
    student_name VARCHAR(100) NOT NULL,  
    student_address VARCHAR(40) default NULL, 
    admission_date DATE,
    score float(4, 1) default NULL, 
    PRIMARY KEY ( student_id )
);
-- 插入数据
INSERT INTO students  
(student_id, student_name, student_address,score, admission_date)  
VALUES(1,'Maxsu','Haikou', 99.5,'2017-01-07 00:00:00');

INSERT INTO students  
(student_id, student_name, student_address, score, admission_date)  
VALUES  
(2,'Crurry','Beijing',86,'2016-05-07 00:00:00'),
(3,'JMaster','Beijing',91,'2016-05-07 00:00:00'),  
(4,'Mahesh','Guangzhou',78,'2016-06-07 00:00:00'),  
(5,'Kobe','Shanghai',89,'2016-02-07 00:00:00'),  
(6,'Blaba','Shengzhen',100,'2016-08-07 00:00:00');

1. AVG()函数与单表达式

示例：

查询Student表的平均分数。参考以下查询语句 -

SELECT AVG(Score) AS "Average  Score" FROM students;

执行上面查询语句，得到以下结果 -

MariaDB [testdb]> SELECT AVG(Score) AS "Average  Score" FROM students;
+----------------+
| Average  Score |
+----------------+
|       90.58333 |
+----------------+
row in set (0.04 sec)

2. AVG()函数与公式

也可以在AVG()函数使用数学公式。 例如，如果要将学生的平均成绩提高50％，则可以使用以下公式来计算：

当前数据库中的记录如下 -

MariaDB [testdb]> select * from students;
+------------+--------------+-----------------+----------------+-------+
| student_id | student_name | student_address | admission_date | score |
+------------+--------------+-----------------+----------------+-------+
|          1 | Maxsu        | Haikou          | 2017-01-07     |  99.5 |
|          2 | Crurry       | Beijing         | 2016-05-07     |  86.0 |
|          3 | JMaster      | Beijing         | 2016-05-07     |  91.0 |
|          4 | Mahesh       | Guangzhou       | 2016-06-07     |  78.0 |
|          5 | Kobe         | Shanghai        | 2016-02-07     |  89.0 |
|          6 | Blaba        | Shengzhen       | 2016-08-07     | 100.0 |
+------------+--------------+-----------------+----------------+-------+
rows in set (0.07 sec)

示例：

SELECT AVG(score * 1.5) AS "New Score"  FROM students;

执行上面查询语句，得到以下结果 -

MariaDB [testdb]> SELECT AVG(score * 1.5) AS "New Score"  FROM students;
+-----------+
| New Score |
+-----------+
| 135.87500 |
+-----------+
row in set (0.01 sec)

2. AVG()函数与Order By子句

为了更容易说明问题，这里再插入一条记录 -

INSERT INTO students  
(student_name, student_address,score, admission_date)  
VALUES('Maxsu','Haikou', 90,'2017-11-17 00:00:00');

当前students表中，有以下数据 -

MariaDB [testdb]> select * from students;
+------------+--------------+-----------------+----------------+-------+
| student_id | student_name | student_address | admission_date | score |
+------------+--------------+-----------------+----------------+-------+
|          1 | Maxsu        | Haikou          | 2017-01-07     |  99.5 |
|          2 | Crurry       | Beijing         | 2016-05-07     |  86.0 |
|          3 | JMaster      | Beijing         | 2016-05-07     |  91.0 |
|          4 | Mahesh       | Guangzhou       | 2016-06-07     |  78.0 |
|          5 | Kobe         | Shanghai        | 2016-02-07     |  89.0 |
|          6 | Blaba        | Shengzhen       | 2016-08-07     | 100.0 |
|          7 | Maxsu        | Haikou          | 2017-11-17     |  90.0 |
+------------+--------------+-----------------+----------------+-------+
rows in set (0.00 sec)

参考下查询语句 -

SELECT student_name, AVG(score) AS "Average Salary"  
FROM students  
GROUP BY student_name;

执行上面查询语句，得到以下结果 -

MariaDB [testdb]> SELECT student_name, AVG(score) AS "Average Salary"
    -> FROM students
    -> GROUP BY student_name;
+--------------+----------------+
| student_name | Average Salary |
+--------------+----------------+
| Blaba        |      100.00000 |
| Crurry       |       86.00000 |
| JMaster      |       91.00000 |
| Kobe         |       89.00000 |
| Mahesh       |       78.00000 |
| Maxsu        |       94.75000 |
+--------------+----------------+
rows in set (0.02 sec)