AVG和SUM
- 可以對數值型資料使用AVG 和 SUM 函數
- 代碼案例
SELECT AVG(salary), SUM(salary), AVG(salary) * 107 FROM employees;
# 錯誤案例:
# 如下的操作沒有意義,因為不是數值類型
SELECT SUM(last_name), AVG(last_name), SUM(hire_date) FROM employees;
MIN和MAX函數
- 可以對任意資料類型的資料使用 MIN 和 MAX 函數
- 代碼案例
SELECT MAX(salary), MIN(salary) FROM employees;
SELECT MAX(last_name), MIN(last_name), MAX(hire_date), MIN(hire_date) FROM employees;
COUNT函數
- COUNT(*)傳回表中記錄總數,适用于任意資料類型
- 代碼案例
# 計算指定字段在查詢結構中出現的個數(不包含NULL值的)
SELECT COUNT(employee_id), COUNT(salary), COUNT(2 * salary), COUNT(1), COUNT(2), COUNT(*) FROM employees;
# 計算表中有多少條記錄
# 方式1:COUNT(*)
# 方式2:COUNT(1)
# 方式3:COUNT(具體字段),不一定對
# 注意:計算指定字段出現的個數時,是不計算NULL值的
SELECT COUNT(commission_pct) FROM employees;
# 公式:AVG = SUM / COUNT
SELECT AVG(salary), SUM(salary)/COUNT(salary),
AVG(commission_pct), SUM(commission_pct)/COUNT(commission_pct),
SUM(commission_pct) / 107
FROM employees;
# 查詢公司中平均獎金率
# 錯誤寫法:如果某些人的獎金為null,則不會計算
SELECT AVG(commission_pct) FROM employees;
# 正确寫法
SELECT SUM(commission_pct) / COUNT(IFNULL(commission_pct,0)),
AVG(IFNULL(commission_pct,0))
FROM employees;
# 如何需要統計表中的記錄數,使用COUNT(*)、COUNT(1)、COUNT(具體字段) 哪個效率更高
# 如果使用的是MyISAM 存儲引擎,則三者效率相同,都是O(1)
# 如果使用的是InnoDB 存儲引擎,則三者效率:COUNT(*) = COUNT(1)> COUNT(字段)
GROUP BY
- 可以使用GROUP BY子句将表中的資料分成若幹組
- 代碼案例
# 查詢各個部門的平均工資,最高工資
SELECT department_id, AVG(salary), SUM(salary) FROM employees GROUP BY department_id
# 查詢各個job_id的平均工資
SELECT job_id, AVG(salary) FROM employees GROUP BY job_id;
# 查詢各個department_id,job_id的平均工資
# 方式1:
SELECT department_id, job_id, AVG(salary) FROM employees GROUP BY department_id, job_id;
# 方式2:
SELECT job_id, department_id, AVG(salary) FROM employees GROUP BY job_id,department_id;
# 錯誤寫法:job_id是非組函數,但沒有寫在group by中
SELECT department_id, job_id, AVG(salary)
FROM employees
GROUP BY department_id;
# 錯誤原因:SELECT中出現的非組函數的字段必須聲明在GROUP BY 中
# 反之,GROUP BY中聲明的字段可以不出現在SELECT中
# GROUP BY 聲明在FROM後面、WHERE後面,ORDER BY 前面、LIMIT前面
# MySQL中GROUP BY中使用WITH ROLLUP,用于統計
SELECT department_id, AVG(salary)
FROM employees
GROUP BY department_id WITH ROLLUP;
# 查詢各個部門的平均工資,按照平均工資升序排列
SELECT department_id, AVG(salary) avg_sal
FROM employees
GROUP BY department_id
ORDER BY avg_sal ASC;
# 當使用ROLLUP時,不能同時使用ORDER BY子句進行結果排序,即ROLLUP和ORDER BY是互相排斥的
# 錯誤寫法
SELECT department_id, AVG(salary) avg_sal
FROM employees
GROUP BY department_id WITH ROLLUP
ORDER BY avg_sal ASC;
HAVING
- 簡介
1. 行已經被分組
2. 使用了聚合函數
3. 滿足HAVING 子句中條件的分組将被顯示
4. HAVING 不能單獨使用,必須要跟 GROUP BY 一起使用
- 代碼案例
# 查詢各個部門中最高工資比10000高的部門資訊
# 錯誤寫法:不能在 WHERE 子句中使用聚合函數
SELECT department_id, MAX(salary)
FROM employees
WHERE MAX(salary) > 10000
GROUP BY department_id;
# 如果過濾條件中使用了聚合函數,則必須使用HAVING來替換WHERE。否則會報錯
# HAVING 必須聲明在 GROUP BY 的後面
#正确的寫法:
SELECT department_id, MAX(salary)
FROM employees
GROUP BY department_id
HAVING MAX(salary) > 10000;
# 開發中,我們使用HAVING的前提是SQL中使用了GROUP BY,也即是說使用了having就必須使用group by
# 查詢部門id為10,20,30,40這4個部門中最高工資比10000高的部門資訊
# 方式1:推薦,執行效率高于方式2
SELECT department_id, MAX(salary)
FROM employees
WHERE department_id IN (10,20,30,40)
GROUP BY department_id
HAVING MAX(salary) > 10000;
#方式2:
SELECT department_id, MAX(salary)
FROM employees
GROUP BY department_id
HAVING MAX(salary) > 10000 AND department_id IN (10,20,30,40);
# 當過濾條件中有聚合函數時,則此過濾條件必須聲明在HAVING中
# 當過濾條件中沒有聚合函數時,則此過濾條件聲明在WHERE中或HAVING中都可以。但建議聲明在WHERE中
/*
* WHERE 與 HAVING 的對比
* 1. 從适用範圍上來講,HAVING的适用範圍更廣。
* 2. 如果過濾條件中沒有聚合函數:這種情況下,WHERE的執行效率要高于HAVING
*/
-
sql語句書寫順序
SELECT ... FROM ... WHERE ... GROUP BY ... HAVING ... ORDER BY ... LIMIT...
-
sql語句執行順序
FROM -> WHERE -> GROUP BY -> HAVING -> SELECT 的字段 -> DISTINCT -> ORDER BY -> LIMIT
# 1. where子句不能使用組函數進行過濾
# 2.查詢公司員工工資的最大值,最小值,平均值,總和
SELECT MAX(salary) max_sal, MIN(salary) mim_sal, AVG(salary) avg_sal, SUM(salary) sum_sal FROM employees;
# 3.查詢各job_id的員工工資的最大值,最小值,平均值,總和
SELECT job_id, MAX(salary), MIN(salary), AVG(salary), SUM(salary) FROM employees GROUP BY job_id;
# 4.選擇具有各個job_id的員勞工數
SELECT job_id, COUNT(*) FROM employees GROUP BY job_id;
# 5.查詢員工最高工資和最低工資的差距(DIFFERENCE)
SELECT MAX(salary) - MIN(salary) "DIFFERENCE" FROM employees;
# 6.查詢各個管理者手下員工的最低工資,其中最低工資不能低于6000,沒有管理者的員工不計算在内
SELECT manager_id, MIN(salary) FROM employees
WHERE manager_id IS NOT NULL
GROUP BY manager_id
HAVING MIN(salary) >= 6000;
# 7.查詢所有部門的名字,location_id,員工數量和平均工資,并按平均工資降序
SELECT d.department_name, d.location_id, COUNT(employee_id), AVG(salary)
FROM departments d LEFT JOIN employees e
ON d.`department_id` = e.`department_id`
GROUP BY department_name, location_id
# 8.查詢每個工種、每個部門的部門名、工種名和最低工資
SELECT d.department_name, e.job_id, MIN(salary)
FROM departments d LEFT JOIN employees e
ON d.`department_id` = e.`department_id`
GROUP BY department_name, job_id