MySQL高效查询:聚合、分组与联合查询
一、聚合查询深度解析
1.1 核心聚合函数家族
MySQL提供五大基础聚合函数构成数据处理基石:
SELECT
COUNT(*) AS total_records, -- 行数统计
SUM(salary) AS total_salary, -- 数值求和
AVG(age) AS average_age, -- 平均值计算
MAX(score) AS highest_score, -- 最大值获取
MIN(join_date) AS earliest_date -- 最小值提取
FROM employees;
特殊场景处理技巧:
-- 统计不重复值
SELECT COUNT(DISTINCT department) AS unique_departments
FROM employees;
-- 安全除法处理(避免除零错误)
SELECT
SUM(sales) / NULLIF(COUNT(*), 0) AS safe_avg
FROM sales_records;
1.2 聚合函数运行机制
查询优化器处理聚合查询的典型执行流程:
- 全表扫描或索引扫描获取数据
- 在内存中构建临时聚合结果集
- 应用过滤条件进行数据筛选
- 返回最终计算结果
性能优化方案对比:
-- 低效写法(全表扫描)
EXPLAIN SELECT AVG(price) FROM products;
-- 优化方案(索引覆盖)
ALTER TABLE products ADD INDEX idx_price (price);
EXPLAIN SELECT AVG(price) FROM products USE INDEX (idx_price);
1.3 多维度聚合实践
组合聚合的典型应用场景:
SELECT
COUNT(*) AS total_orders,
SUM(amount) AS total_sales,
AVG(amount) AS avg_order_value,
MAX(amount) AS max_single_order
FROM orders
WHERE order_date BETWEEN '2023-01-01' AND '2023-12-31';
二、分组查询进阶技巧
2.1 GROUP BY原理剖析
分组查询执行过程分解:
- 数据读取(全表/索引)
- 临时分组表构建
- 聚合计算执行
- 结果集过滤
- 最终结果返回
多字段分组示例:
SELECT
department_id,
job_title,
COUNT(*) AS employee_count,
AVG(salary) AS avg_salary
FROM employees
GROUP BY department_id, job_title
ORDER BY department_id, job_title;
2.2 HAVING与WHERE对比
两种过滤方式的差异对比实验:
-- 使用WHERE过滤原始数据
SELECT department, AVG(salary)
FROM employees
WHERE salary > 5000
GROUP BY department;
-- 使用HAVING过滤聚合结果
SELECT department, AVG(salary)
FROM employees
GROUP BY department
HAVING AVG(salary) > 8000;
2.3 高级分组功能
WITH ROLLUP实现多维分析:
SELECT
YEAR(order_date) AS order_year,
QUARTER(order_date) AS order_quarter,
SUM(amount) AS total_sales
FROM orders
GROUP BY order_year, order_quarter WITH ROLLUP;
分组排序优化方案:
SELECT
department,
COUNT(*) AS emp_count,
AVG(salary) AS avg_salary
FROM employees
GROUP BY department
ORDER BY avg_salary DESC;
三、联合查询深度应用
3.1 UNION核心机制
UNION执行流程解析:
- 执行各个子查询
- 合并结果集
- 去重处理(UNION)
- 最终排序输出
性能对比测试:
-- UNION去重版本
SELECT * FROM table1
UNION
SELECT * FROM table2;
-- UNION ALL快速版本
SELECT * FROM table1
UNION ALL
SELECT * FROM table2;
3.2 复杂联合查询实践
多表联合示例:
(
SELECT
'Q1' AS quarter,
product_id,
SUM(quantity) AS total_sales
FROM sales_q1
GROUP BY product_id
)
UNION ALL
(
SELECT
'Q2' AS quarter,
product_id,
SUM(quantity) AS total_sales
FROM sales_q2
GROUP BY product_id
)
ORDER BY quarter, total_sales DESC;
3.3 联合查询优化策略
索引优化案例:
-- 原始查询
SELECT id FROM users_2022
UNION
SELECT id FROM users_2023;
-- 优化方案
ALTER TABLE users_2022 ADD INDEX idx_id (id);
ALTER TABLE users_2023 ADD INDEX idx_id (id);
EXPLAIN SELECT id FROM users_2022
UNION
SELECT id FROM users_2023;
四、综合应用实战
4.1 电商数据分析案例
多表关联分析查询:
SELECT
c.category_name,
COUNT(o.order_id) AS order_count,
SUM(oi.quantity * oi.unit_price) AS total_sales,
AVG(oi.quantity) AS avg_quantity
FROM orders o
JOIN order_items oi ON o.order_id = oi.order_id
JOIN products p ON oi.product_id = p.product_id
JOIN categories c ON p.category_id = c.category_id
WHERE o.order_date BETWEEN '2023-01-01' AND '2023-12-31'
GROUP BY c.category_id
HAVING total_sales > 100000
ORDER BY total_sales DESC;
4.2 查询性能优化方案
执行计划分析示例:
EXPLAIN
SELECT
department,
COUNT(*) AS emp_count,
AVG(salary) AS avg_salary
FROM employees
WHERE hire_date > '2010-01-01'
GROUP BY department
HAVING avg_salary > 5000;
索引优化策略:
-- 创建复合索引
ALTER TABLE employees ADD INDEX idx_dept_hire_salary (department, hire_date, salary);
-- 优化后的查询执行计划分析
EXPLAIN
SELECT
department,
COUNT(*) AS emp_count,
AVG(salary) AS avg_salary
FROM employees
WHERE hire_date > '2010-01-01'
GROUP BY department
HAVING avg_salary > 5000;
五、最佳实践与常见陷阱
5.1 常见错误分析
错误案例1:分组字段遗漏
-- 错误写法
SELECT department, employee_name, AVG(salary)
FROM employees
GROUP BY department;
-- 正确写法
SELECT department, employee_name, AVG(salary)
FROM employees
GROUP BY department, employee_name;
错误案例2:隐式排序依赖
-- 不可靠的排序方式
SELECT department, COUNT(*)
FROM employees
GROUP BY department;
-- 显式指定排序
SELECT department, COUNT(*)
FROM employees
GROUP BY department
ORDER BY department;
5.2 进阶技巧总结
- 聚合函数嵌套技巧:
SELECT
MAX(avg_salary) AS max_avg_salary
FROM (
SELECT
department,
AVG(salary) AS avg_salary
FROM employees
GROUP BY department
) AS dept_salaries;
- 条件聚合实现:
SELECT
department,
COUNT(*) AS total_employees,
SUM(CASE WHEN salary > 10000 THEN 1 ELSE 0 END) AS high_earners
FROM employees
GROUP BY department;
- 分组连接字符串:
SELECT
department,
GROUP_CONCAT(DISTINCT job_title ORDER BY job_title SEPARATOR ' | ') AS positions
FROM employees
GROUP BY department;
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