Question

致敬，

我是MySQL的新手，特别是生成查询，我想知道是否有可能让我的查询执行得更快？我在这里使用员工数据库：https://github.com/datacharmer/test_db

现在我必须提出的查询需要回答以下问题：＆＃34;•对于每个部门，列出每十年出生的员工人数及其平均工资＆＃34;

这就是我提出的：

SELECT DISTINCT d.dept_name, count(e.emp_no), AVG(s.salary), ROUND(YEAR(e.birth_date), -1) AS birth_date 
FROM employees e, departments d, salaries s, dept_emp de 
WHERE de.emp_no = e.emp_no AND de.dept_no = d.dept_no 
    AND e.emp_no = s.emp_no 
    GROUP BY d.dept_name, 
    ROUND(YEAR(e.birth_date), -1);

它有效，它产生教授想要的结果，但它很慢，大约需要11秒才能执行。我的查询中是否存在执行缓慢的问题？

编辑：

描述的表：

mysql> explain dept_emp_latest_date;
+-----------+---------+------+-----+---------+-------+
| Field     | Type    | Null | Key | Default | Extra |
+-----------+---------+------+-----+---------+-------+
| emp_no    | int(11) | NO   |     | NULL    |       |
| from_date | date    | YES  |     | NULL    |       |
| to_date   | date    | YES  |     | NULL    |       |
+-----------+---------+------+-----+---------+-------+
3 rows in set (0.01 sec)

mysql> explain dept_manager
    -> ;
+-----------+---------+------+-----+---------+-------+
| Field     | Type    | Null | Key | Default | Extra |
+-----------+---------+------+-----+---------+-------+
| emp_no    | int(11) | NO   | PRI | NULL    |       |
| dept_no   | char(4) | NO   | PRI | NULL    |       |
| from_date | date    | NO   |     | NULL    |       |
| to_date   | date    | NO   |     | NULL    |       |
+-----------+---------+------+-----+---------+-------+
4 rows in set (0.00 sec)

mysql> explain employees;
+------------+---------------+------+-----+---------+-------+
| Field      | Type          | Null | Key | Default | Extra |
+------------+---------------+------+-----+---------+-------+
| emp_no     | int(11)       | NO   | PRI | NULL    |       |
| birth_date | date          | NO   |     | NULL    |       |
| first_name | varchar(14)   | NO   |     | NULL    |       |
| last_name  | varchar(16)   | NO   |     | NULL    |       |
| gender     | enum('M','F') | NO   |     | NULL    |       |
| hire_date  | date          | NO   |     | NULL    |       |
+------------+---------------+------+-----+---------+-------+
6 rows in set (0.00 sec)

mysql> explain salaries;
+-----------+---------+------+-----+---------+-------+
| Field     | Type    | Null | Key | Default | Extra |
+-----------+---------+------+-----+---------+-------+
| emp_no    | int(11) | NO   | PRI | NULL    |       |
| salary    | int(11) | NO   |     | NULL    |       |
| from_date | date    | NO   | PRI | NULL    |       |
| to_date   | date    | NO   |     | NULL    |       |
+-----------+---------+------+-----+---------+-------+
4 rows in set (0.00 sec)

mysql> explain titles;
+-----------+-------------+------+-----+---------+-------+
| Field     | Type        | Null | Key | Default | Extra |
+-----------+-------------+------+-----+---------+-------+
| emp_no    | int(11)     | NO   | PRI | NULL    |       |
| title     | varchar(50) | NO   | PRI | NULL    |       |
| from_date | date        | NO   | PRI | NULL    |       |
| to_date   | date        | YES  |     | NULL    |       |
+-----------+-------------+------+-----+---------+-------+
4 rows in set (0.00 sec)

mysql> explain departments;
+-----------+-------------+------+-----+---------+-------+
| Field     | Type        | Null | Key | Default | Extra |
+-----------+-------------+------+-----+---------+-------+
| dept_no   | char(4)     | NO   | PRI | NULL    |       |
| dept_name | varchar(40) | NO   | UNI | NULL    |       |
+-----------+-------------+------+-----+---------+-------+
2 rows in set (0.01 sec)

mysql> explain current_dept_emp;
+-----------+---------+------+-----+---------+-------+
| Field     | Type    | Null | Key | Default | Extra |
+-----------+---------+------+-----+---------+-------+
| emp_no    | int(11) | NO   |     | NULL    |       |
| dept_no   | char(4) | NO   |     | NULL    |       |
| from_date | date    | YES  |     | NULL    |       |
| to_date   | date    | YES  |     | NULL    |       |
+-----------+---------+------+-----+---------+-------+
4 rows in set (0.02 sec)

mysql> explain dept_emp;
+-----------+---------+------+-----+---------+-------+
| Field     | Type    | Null | Key | Default | Extra |
+-----------+---------+------+-----+---------+-------+
| emp_no    | int(11) | NO   | PRI | NULL    |       |
| dept_no   | char(4) | NO   | PRI | NULL    |       |
| from_date | date    | NO   |     | NULL    |       |
| to_date   | date    | NO   |     | NULL    |       |
+-----------+---------+------+-----+---------+-------+
4 rows in set (0.00 sec)

Answer 1

您的查询重构为使用21世纪的JOIN语法。

SELECT DISTINCT d.dept_name, count(e.emp_no), AVG(s.salary),
       ROUND(YEAR(e.birth_date), -1) AS birth_date 
  FROM employees e
  JOIN salaries s ON e.emp_no = s.emp_no
  JOIN dept_emp de  ON de.emp_no = e.emp_no 
  JOIN departments d ON de.dept_no = d.dept_no
 GROUP BY d.dept_name, ROUND(YEAR(e.birth_date), -1);

请注意，DISTINCT在聚合（GROUP BY）查询中是多余的。摆脱它需要几秒钟。

但请注意salaries表包含历史薪资数据。每行包含from_date和to_date。 from_date列是该表的主键的一部分以及员工编号。因此，您的查询会不加区分地平均一大堆薪资数据，并且会记录太多的记录。

此查询需要4.6秒左右（我的机器速度与您的相同，第一次查询需要11秒）。对于您提供的数据，它更有意义，因为它会提取特定时间点的工资记录和部门关联记录，而不是处理整个数据。

SELECT d.dept_name, COUNT(e.emp_no), AVG(s.salary),
       ROUND(YEAR(e.birth_date), -1) AS birth_date
  FROM employees e
  JOIN salaries s ON e.emp_no = s.emp_no
  JOIN dept_emp de ON de.emp_no = e.emp_no
  JOIN departments d ON de.dept_no = d.dept_no
 WHERE s.from_date<='2014-01-01' AND s.to_date >'2014-01-01'
   AND de.from_date<='2014-01-01' AND de.to_date >'2014-01-01'
 GROUP BY d.dept_name, ROUND(YEAR(e.birth_date), -1);

它正在处理25万个员工记录，因此它每毫秒处理52个记录。对笔记本电脑来说还不错。

是否可以更快地进行此查询？

1 个答案: