MySQL之子查询（DQL）

SELECT last_name,job_id,salary FROM employees WHERE job_id = (
SELECT job_id FROM employees WHERE employee_id = 130
) AND salary > (
SELECT salary FROM employees WHERE employee_id = 140
);

SELECT last_name,job_id,salary FROM employees WHERE salary =
(SELECT MIN(salary) FROM employees);

#多行子查询使用单行比较符
SELECT employee_id,last_name FROM employees WHERE salary = (SELECT MIN(salary) FROM employees GROUP BY department_id);

SELECT last_name FROM employees
WHERE department_id <> ALL
(SELECT DISTINCT department_id FROM departments WHERE location_id IN (1400,1700));

SELECT employee_id,last_name,job_id,salary FROM employees
WHERE salary <ANY
(SELECT salary FROM employees WHERE job_id = ‘IT_PROG‘)
AND job_id <> ‘IT_PROG‘;

SELECT employee_id,last_name,job_id,salary FROM employees 
WHERE salary < ALL
(SELECT salary FROM employees WHERE job_id = ‘IT_PROG‘)
AND job_id <> ‘IT_PROG‘;

SELECT emp.last_name FROM employees emp WHERE emp.employee_id NOT IN
(SELECT mgr.manager_id FROM employees mgr);

#一.where或having后面
/*
 * 1.标量子查询（单行子查询）
 * 2.列子查询（多行子查询）
 * 3.行子查询（多列多行）
 * 
 * 特点：
 * ①子查询放在小括号内
 * ②子查询一般放在条件的右侧
 * ③标量子查询，一般搭配着单行操作符使用 > < >= <= = <>
 *  列子查询,一般搭配着多行操作符使用 in、any/some、all
 * ④子查询的执行优先于主查询执行，主查询的条件用到了子查询的结果
 */
#1.标量子查询
#案例1：谁的工资比Sciarra高？
#①查询Sciarra的工资
SELECT salary FROM employees WHERE last_name = ‘Sciarra‘;
#②查询员工的信息，满足salary>①结果
SELECT * FROM employees WHERE salary > (SELECT salary FROM employees WHERE last_name = ‘Sciarra‘);


#案例2：返回job_id与130号员工相同，salary比140号员工多的员工姓名、job_id和工资
#①查询130号员工的job_id
SELECT job_id FROM employees WHERE employee_id = 130;
#②查询140号员工的salary
SELECT salary FROM employees WHERE employee_id = 140;
#③查询员工的姓名，job_id和工资，要求job_id=①并且salary>②
SELECT last_name,job_id,salary FROM employees
WHERE job_id = (
SELECT job_id FROM employees WHERE employee_id = 130
) AND salary>(
SELECT salary FROM employees WHERE employee_id = 140
);


#案例3：返回公司工资最少的员工的last_name、job_id和salary
#①查询公司的最低工资
SELECT MIN(salary) FROM employees;
#②查询last_name、job_id和salary，要求salary=①
SELECT last_name,job_id,salary FROM employees WHERE salary = (SELECT MIN(salary) FROM employees);


#案例4：查询最低工资大于50号部门最低工资的部门id和其最低工资
#①查询50号部门的最低工资
SELECT MIN(salary) FROM employees WHERE department_id = 50;
#②查询每个部门的最低工资
SELECT MIN(salary),department_id FROM employees GROUP BY department_id;
#③在②基础上筛选，满足min(salary)>①
SELECT MIN(salary),department_id FROM employees GROUP BY department_id
HAVING MIN(salary) > (SELECT  MIN(salary) FROM employees WHERE department_id = 50);


#非法使用标量子查询
SELECT MIN(salary),department_id FROM employees GROUP BY department_id
HAVING MIN(salary)>(SELECT  salary FROM employees WHERE department_id = 70);


#2.列子查询（多行子查询）
#案例1：返回location_id是1400或1700的部门中的所有员工姓名
#①查询location_id是1400或1700的部门编号
SELECT DISTINCT department_id FROM departments WHERE location_id IN(1400,1700);
#②查询员工姓名，要求部门号是①列表中的某一个
SELECT last_name FROM employees WHERE department_id <> ALL (SELECT DISTINCT department_id FROM departments WHERE location_id IN(1400,1700));


#案例2：返回其它工种中比job_id为IT_PROG工种任一工资低的员工的员工号、姓名、job_id以及salary
#①查询job_id为IT_PROG部门任一工资
SELECT DISTINCT salary FROM employees WHERE job_id = ‘IT_PROG‘;
#②查询员工号、姓名、job_id以及salary，salary<(①)的任意一个
SELECT last_name,employee_id,job_id,salary FROM employees WHERE salary < ANY (
SELECT DISTINCT salary FROM employees WHERE job_id = ‘IT_PROG‘) 
AND job_id<>‘IT_PROG‘;
#或
SELECT last_name,employee_id,job_id,salary FROM employees WHERE salary < (
SELECT MAX(salary) FROM employees WHERE job_id = ‘IT_PROG‘
) AND job_id<>‘IT_PROG‘;


#案例3：返回其它部门中比job_id为IT_PROG部门所有工资都低的员工的员工号、姓名、job_id以及salary
SELECT last_name,employee_id,job_id,salary FROM employees
WHERE salary < ALL (
SELECT DISTINCT salary FROM employees WHERE job_id = ‘IT_PROG‘
) AND job_id<>‘IT_PROG‘;
#或
SELECT last_name,employee_id,job_id,salary FROM employees
WHERE salary<(
SELECT MIN( salary) FROM employees WHERE job_id = ‘IT_PROG‘
) AND job_id<>‘IT_PROG‘;


#3.行子查询（结果集一行多列或多行多列）
#案例：查询员工编号最小并且工资最高的员工信息
SELECT * FROM employees WHERE (employee_id,salary)=(
SELECT MIN(employee_id),MAX(salary) FROM employees
);
#①查询最小的员工编号
SELECT MIN(employee_id) FROM employees;
#②查询最高工资
SELECT MAX(salary) FROM employees;
#③查询员工信息
SELECT * FROM employees WHERE employee_id = (
SELECT MIN(employee_id) FROM employees
)AND salary=(
SELECT MAX(salary) FROM employees
);


#二.select后面
/*
 * 仅仅支持标量子查询
*/
#案例1：查询每个部门的员工个数
SELECT d.*,(SELECT COUNT(*) FROM employees e WHERE e.department_id = d.department_id) 个数 FROM departments d;


#案例2：查询员工号=102的部门名
SELECT department_name,e.department_id FROM departments d 
INNER JOIN employees e ON d.department_id=e.department_id
WHERE e.employee_id=102;


#三.from后面
/*
 * 将子查询结果充当一张表，要求必须起别名
 */
#案例：查询每个部门的平均工资的工资等级
#①查询每个部门的平均工资
SELECT AVG(salary),department_id FROM employees GROUP BY department_id;

SELECT * FROM jobs;

#②连接①的结果集和job_grades表，筛选条件平均工资 between lowest_sal and highest_sal
SELECT ag_dep.*,g.job_title
FROM (
SELECT AVG(salary) ag,department_id FROM employees GROUP BY department_id
) ag_dep
INNER JOIN jobs g ON ag_dep.ag BETWEEN min_salary AND max_salary;


#四.exists后面（相关子查询）
/*
 * 语法：
 * exists(完整的查询语句)
 * 结果：1或0
 */
SELECT EXISTS(SELECT employee_id FROM employees WHERE salary=300000);

#案例1：查询有员工的部门名
#in
SELECT department_name FROM departments d
WHERE d.department_id IN(SELECT department_id FROM employees);
#exists
SELECT department_name FROM departments d
WHERE EXISTS(
SELECT * FROM employees e WHERE d.department_id=e.department_id
);


#案例2：查询没有女朋友的男神信息
#in
SELECT bo.* FROM boys bo WHERE bo.id NOT IN(SELECT boyfriend_id FROM beauty);
#exists
SELECT bo.* FROM boys bo WHERE NOT EXISTS(SELECT boyfriend_id FROM beauty b WHERE bo.id=b.boyfriend_id);

#============================================================================
#1.查询和Zlotkey相同部门的员工姓名和工资
#①查询Zlotkey的部门
SELECT department_id FROM employees WHERE last_name = ‘K_ing‘;
#②查询部门号=①的姓名和工资
SELECT last_name,salary FROM employees
WHERE department_id = (SELECT department_id FROM employees WHERE last_name = ‘K_ing‘);


#2.查询工资比公司平均工资高的员工的员工号，姓名和工资
#①查询平均工资
SELECT AVG(salary) FROM employees;
#②查询工资>①的员工号，姓名和工资
SELECT last_name,employee_id,salary FROM employees WHERE salary > (
SELECT AVG(salary) FROM employees
);


#3.查询各部门中工资比本部门平均工资高的员工的员工号, 姓名和工资
#①查询各部门的平均工资
SELECT AVG(salary),department_id FROM employees GROUP BY department_id;
#②连接①结果集和employees表，进行筛选
SELECT employee_id,last_name,salary,e.department_id FROM employees e
INNER JOIN (SELECT AVG(salary) ag,department_id FROM employees GROUP BY department_id
) ag_dep ON e.department_id = ag_dep.department_id WHERE salary>ag_dep.ag;


#4.查询和姓名中包含字母u的员工在相同部门的员工的员工号和姓名
#①查询姓名中包含字母u的员工的部门
SELECT  DISTINCT department_id FROM employees WHERE last_name LIKE ‘%u%‘;
#②查询部门号=①中的任意一个的员工号和姓名
SELECT last_name,employee_id FROM employees
WHERE department_id IN(
SELECT  DISTINCT department_id FROM employees WHERE last_name LIKE ‘%u%‘
);


#5.查询在部门的location_id为1700的部门工作的员工的员工号
#①查询location_id为1700的部门
SELECT DISTINCT department_id FROM departments WHERE location_id  = 1700;
#②查询部门号=①中的任意一个的员工号
SELECT employee_id FROM employees
WHERE department_id =ANY(
SELECT DISTINCT department_id FROM departments WHERE location_id  = 1700
);


#6.查询管理者是King的员工姓名和工资
#①查询姓名为king的员工编号
SELECT employee_id FROM employees WHERE last_name  = ‘K_ing‘;
#②查询哪个员工的manager_id = ①
SELECT last_name,salary FROM employees
WHERE manager_id IN(
SELECT employee_id FROM employees WHERE last_name  = ‘K_ing‘
);


#7.查询工资最高的员工的姓名，要求first_name和last_name显示为一列，列名为姓.名
#①查询最高工资
SELECT MAX(salary) FROM employees;
#②查询工资=①的姓.名
SELECT CONCAT(first_name,last_name) "姓.名" FROM employees
WHERE salary=(SELECT MAX(salary) FROM employees);
#======================================================================
#1.查询工资最低的员工信息：last_name, salary
#①查询最低的工资
SELECT MIN(salary) FROM employees;
#②查询last_name,salary，要求salary=①
SELECT last_name,salary FROM employees WHERE salary=(SELECT MIN(salary) FROM employees);


#2.查询平均工资最低的部门信息
#方式一：
#①各部门的平均工资
SELECT AVG(salary),department_id FROM employees GROUP BY department_id;
#②查询①结果上的最低平均工资
SELECT MIN(ag) FROM (
SELECT AVG(salary) ag,department_id FROM employees GROUP BY department_id
) ag_dep;
#③查询哪个部门的平均工资=②
SELECT AVG(salary),department_id FROM employees GROUP BY department_id
HAVING AVG(salary)=(
SELECT MIN(ag) FROM (SELECT AVG(salary) ag,department_id FROM employees GROUP BY department_id) ag_dep);
#④查询部门信息
SELECT d.* FROM departments d WHERE d.department_id=(
SELECT department_id FROM employees GROUP BY department_id HAVING AVG(salary) = (
SELECT MIN(ag) FROM (SELECT AVG(salary) ag,department_id FROM employees GROUP BY department_id) ag_dep)
);


#方式二：
#①各部门的平均工资
SELECT AVG(salary),department_id FROM employees GROUP BY department_id;
#②求出最低平均工资的部门编号
SELECT department_id FROM employees GROUP BY department_id ORDER BY AVG(salary) LIMIT 1;
#③查询部门信息
SELECT * FROM departments WHERE department_id=(
SELECT department_id FROM employees GROUP BY department_id ORDER BY AVG(salary) LIMIT 1
);


#3.查询平均工资最低的部门信息和该部门的平均工资
#①各部门的平均工资
SELECT AVG(salary),department_id FROM employees GROUP BY department_id;
#②求出最低平均工资的部门编号
SELECT AVG(salary),department_id FROM employees GROUP BY department_id ORDER BY AVG(salary) LIMIT 1;
#③查询部门信息
SELECT d.*,ag FROM departments d
JOIN (SELECT AVG(salary) ag,department_id FROM employees GROUP BY department_id ORDER BY AVG(salary) LIMIT 1
) ag_dep ON d.department_id=ag_dep.department_id;


#4.查询平均工资最高的job信息
#①查询最高的job的平均工资
SELECT AVG(salary),job_id FROM employees GROUP BY job_id ORDER BY AVG(salary) DESC LIMIT 1;
#②查询job信息
SELECT * FROM jobs WHERE job_id=(
SELECT job_id FROM employees GROUP BY job_id ORDER BY AVG(salary) DESC LIMIT 1);


#5.查询平均工资高于公司平均工资的部门有哪些？
#①查询平均工资
SELECT AVG(salary) FROM employees;
#②查询每个部门的平均工资
SELECT AVG(salary),department_id FROM employees GROUP BY department_id;
#③筛选②结果集，满足平均工资>①
SELECT AVG(salary),department_id FROM employees GROUP BY department_id
HAVING AVG(salary)>(SELECT AVG(salary) FROM employees);


#6.查询出公司中所有manager的详细信息.
#①查询所有manager的员工编号
SELECT DISTINCT manager_id FROM employees;
#②查询详细信息，满足employee_id=①
SELECT * FROM employees WHERE employee_id =ANY(SELECT DISTINCT manager_id FROM employees);


#7.各个部门中最高工资中最低的那个部门的、最低工资是多少？
#①查询各部门的最高工资中最低的部门编号
SELECT department_id FROM employees GROUP BY department_id ORDER BY MAX(salary) LIMIT 1;
#②查询①结果的那个部门的最低工资
SELECT MIN(salary) ,department_id FROM employees
WHERE department_id=(SELECT department_id FROM employees GROUP BY department_id ORDER BY MAX(salary) LIMIT 1);


#8.查询平均工资最高的部门的manager的详细信息：last_name,、department_id、email、salary
#①查询平均工资最高的部门编号
SELECT department_id FROM employees GROUP BY department_id ORDER BY AVG(salary) DESC LIMIT 1;
#②将employees和departments连接查询，筛选条件是①
SELECT last_name, d.department_id, email, salary 
FROM employees e INNER JOIN departments d ON d.manager_id = e.employee_id 
WHERE d.department_id = (SELECT department_id FROM employees GROUP BY department_id ORDER BY AVG(salary) DESC LIMIT 1);

#beauty表
CREATE TABLE beauty (
  id int(100) NOT NULL AUTO_INCREMENT,
  name varchar(255) DEFAULT NULL,
  sex varchar(255) DEFAULT NULL,
  boyfriend_id varchar(255) DEFAULT NULL,
  PRIMARY KEY (id)
) ENGINE=InnoDB AUTO_INCREMENT=13 DEFAULT CHARSET=utf8;
#beauty数据
INSERT INTO beauty VALUES (‘1‘, ‘柳岩‘, ‘女‘, ‘8‘);
INSERT INTO beauty VALUES (‘2‘, ‘苍老师‘, ‘女‘, ‘9‘);
INSERT INTO beauty VALUES (‘3‘, ‘Angelababy‘, ‘女‘, ‘3‘);
INSERT INTO beauty VALUES (‘4‘, ‘热巴‘, ‘女‘, ‘2‘);
INSERT INTO beauty VALUES (‘5‘, ‘周冬际‘, ‘女‘, ‘9‘);
INSERT INTO beauty VALUES (‘6‘, ‘周芷若‘, ‘女‘, ‘1‘);
INSERT INTO beauty VALUES (‘7‘, ‘岳灵珊‘, ‘女‘, ‘9‘);
INSERT INTO beauty VALUES (‘8‘, ‘小昭‘, ‘女‘, ‘1‘);
INSERT INTO beauty VALUES (‘9‘, ‘双儿‘, ‘女‘, ‘9‘);
INSERT INTO beauty VALUES (‘10‘, ‘王语嫣‘, ‘女‘, ‘4‘);
INSERT INTO beauty VALUES (‘11‘, ‘夏雪‘, ‘女‘, ‘9‘);
INSERT INTO beauty VALUES (‘12‘, ‘赵敏‘, ‘女‘, ‘1‘);

#boys表
CREATE TABLE boys (
  id int(100) NOT NULL AUTO_INCREMENT,
  boyName varchar(255) DEFAULT NULL,
  userCP varchar(255) DEFAULT NULL,
  PRIMARY KEY (id)
) ENGINE=InnoDB AUTO_INCREMENT=6 DEFAULT CHARSET=utf8;
#boys数据
INSERT INTO boys VALUES (‘1‘, ‘张无忌‘, ‘100‘);
INSERT INTO boys VALUES (‘2‘, ‘鹿晗‘, ‘800‘);
INSERT INTO boys VALUES (‘3‘, ‘黄晓明‘, ‘50‘);
INSERT INTO boys VALUES (‘4‘, ‘段誉‘, ‘300‘);
INSERT INTO boys VALUES (‘5‘, ‘展昭‘, ‘500‘);

#departments表
CREATE TABLE departments (
  department_id int(4) NOT NULL AUTO_INCREMENT,
  department_name varchar(3) DEFAULT NULL,
  manager_id int(6) DEFAULT NULL,
  location_id int(4) DEFAULT NULL,
  PRIMARY KEY (department_id),
  KEY loc_id_fk (location_id),
  CONSTRAINT loc_id_fk FOREIGN KEY (location_id) REFERENCES locations (location_id)
) ENGINE=InnoDB AUTO_INCREMENT=271 DEFAULT CHARSET=gb2312;
#departments数据
INSERT INTO departments VALUES (‘10‘, ‘Adm‘, ‘200‘, ‘1700‘);
INSERT INTO departments VALUES (‘20‘, ‘Mar‘, ‘201‘, ‘1800‘);
INSERT INTO departments VALUES (‘30‘, ‘Pur‘, ‘114‘, ‘1700‘);
INSERT INTO departments VALUES (‘40‘, ‘Hum‘, ‘203‘, ‘2400‘);
INSERT INTO departments VALUES (‘50‘, ‘Shi‘, ‘121‘, ‘1500‘);
INSERT INTO departments VALUES (‘60‘, ‘IT‘, ‘103‘, ‘1400‘);
INSERT INTO departments VALUES (‘70‘, ‘Pub‘, ‘204‘, ‘2700‘);
INSERT INTO departments VALUES (‘80‘, ‘Sal‘, ‘145‘, ‘2500‘);
INSERT INTO departments VALUES (‘90‘, ‘Exe‘, ‘100‘, ‘1700‘);
INSERT INTO departments VALUES (‘100‘, ‘Fin‘, ‘108‘, ‘1700‘);
INSERT INTO departments VALUES (‘110‘, ‘Acc‘, ‘205‘, ‘1700‘);
INSERT INTO departments VALUES (‘120‘, ‘Tre‘, null, ‘1700‘);
INSERT INTO departments VALUES (‘130‘, ‘Cor‘, null, ‘1700‘);
INSERT INTO departments VALUES (‘140‘, ‘Con‘, null, ‘1700‘);
INSERT INTO departments VALUES (‘150‘, ‘Sha‘, null, ‘1700‘);
INSERT INTO departments VALUES (‘160‘, ‘Ben‘, null, ‘1700‘);
INSERT INTO departments VALUES (‘170‘, ‘Man‘, null, ‘1700‘);
INSERT INTO departments VALUES (‘180‘, ‘Con‘, null, ‘1700‘);
INSERT INTO departments VALUES (‘190‘, ‘Con‘, null, ‘1700‘);
INSERT INTO departments VALUES (‘200‘, ‘Ope‘, null, ‘1700‘);
INSERT INTO departments VALUES (‘210‘, ‘IT ‘, null, ‘1700‘);
INSERT INTO departments VALUES (‘220‘, ‘NOC‘, null, ‘1700‘);
INSERT INTO departments VALUES (‘230‘, ‘IT ‘, null, ‘1700‘);
INSERT INTO departments VALUES (‘240‘, ‘Gov‘, null, ‘1700‘);
INSERT INTO departments VALUES (‘250‘, ‘Ret‘, null, ‘1700‘);
INSERT INTO departments VALUES (‘260‘, ‘Rec‘, null, ‘1700‘);
INSERT INTO departments VALUES (‘270‘, ‘Pay‘, null, ‘1700‘);

#employees表
CREATE TABLE employees (
  employee_id int(6) NOT NULL AUTO_INCREMENT,
  first_name varchar(20) DEFAULT NULL,
  last_name varchar(25) DEFAULT NULL,
  email varchar(25) DEFAULT NULL,
  phone_number varchar(20) DEFAULT NULL,
  job_id varchar(10) DEFAULT NULL,
  salary double(10,2) DEFAULT NULL,
  commission_pct double(4,2) DEFAULT NULL,
  manager_id int(6) DEFAULT NULL,
  department_id int(4) DEFAULT NULL,
  hiredate datetime DEFAULT NULL,
  PRIMARY KEY (employee_id)
) ENGINE=InnoDB AUTO_INCREMENT=207 DEFAULT CHARSET=utf8;
#employees数据
INSERT INTO employees VALUES (‘100‘, ‘Steven‘, ‘K_ing‘, ‘SKING‘, ‘515.123.4567‘, ‘AD_PRES‘, ‘24000.00‘, null, null, ‘90‘, ‘1992-04-03 00:00:00‘);
INSERT INTO employees VALUES (‘101‘, ‘Neena‘, ‘Kochhar‘, ‘NKOCHHAR‘, ‘515.123.4568‘, ‘AD_VP‘, ‘17000.00‘, null, ‘100‘, ‘90‘, ‘1992-04-03 00:00:00‘);
INSERT INTO employees VALUES (‘102‘, ‘Lex‘, ‘De Haan‘, ‘LDEHAAN‘, ‘515.123.4569‘, ‘AD_VP‘, ‘17000.00‘, null, ‘100‘, ‘90‘, ‘1992-04-03 00:00:00‘);
INSERT INTO employees VALUES (‘103‘, ‘Alexander‘, ‘Hunold‘, ‘AHUNOLD‘, ‘590.423.4567‘, ‘IT_PROG‘, ‘9000.00‘, null, ‘102‘, ‘60‘, ‘1992-04-03 00:00:00‘);
INSERT INTO employees VALUES (‘104‘, ‘Bruce‘, ‘Ernst‘, ‘BERNST‘, ‘590.423.4568‘, ‘IT_PROG‘, ‘6000.00‘, null, ‘103‘, ‘60‘, ‘1992-04-03 00:00:00‘);
INSERT INTO employees VALUES (‘105‘, ‘David‘, ‘Austin‘, ‘DAUSTIN‘, ‘590.423.4569‘, ‘IT_PROG‘, ‘4800.00‘, null, ‘103‘, ‘60‘, ‘1998-03-03 00:00:00‘);
INSERT INTO employees VALUES (‘106‘, ‘Valli‘, ‘Pataballa‘, ‘VPATABAL‘, ‘590.423.4560‘, ‘IT_PROG‘, ‘4800.00‘, null, ‘103‘, ‘60‘, ‘1998-03-03 00:00:00‘);
INSERT INTO employees VALUES (‘107‘, ‘Diana‘, ‘Lorentz‘, ‘DLORENTZ‘, ‘590.423.5567‘, ‘IT_PROG‘, ‘4200.00‘, null, ‘103‘, ‘60‘, ‘1998-03-03 00:00:00‘);
INSERT INTO employees VALUES (‘108‘, ‘Nancy‘, ‘Greenberg‘, ‘NGREENBE‘, ‘515.124.4569‘, ‘FI_MGR‘, ‘12000.00‘, null, ‘101‘, ‘100‘, ‘1998-03-03 00:00:00‘);
INSERT INTO employees VALUES (‘109‘, ‘Daniel‘, ‘Faviet‘, ‘DFAVIET‘, ‘515.124.4169‘, ‘FI_ACCOUNT‘, ‘9000.00‘, null, ‘108‘, ‘100‘, ‘1998-03-03 00:00:00‘);
INSERT INTO employees VALUES (‘110‘, ‘John‘, ‘Chen‘, ‘JCHEN‘, ‘515.124.4269‘, ‘FI_ACCOUNT‘, ‘8200.00‘, null, ‘108‘, ‘100‘, ‘2000-09-09 00:00:00‘);
INSERT INTO employees VALUES (‘111‘, ‘Ismael‘, ‘Sciarra‘, ‘ISCIARRA‘, ‘515.124.4369‘, ‘FI_ACCOUNT‘, ‘7700.00‘, null, ‘108‘, ‘100‘, ‘2000-09-09 00:00:00‘);
INSERT INTO employees VALUES (‘112‘, ‘Jose Manuel‘, ‘Urman‘, ‘JMURMAN‘, ‘515.124.4469‘, ‘FI_ACCOUNT‘, ‘7800.00‘, null, ‘108‘, ‘100‘, ‘2000-09-09 00:00:00‘);
INSERT INTO employees VALUES (‘113‘, ‘Luis‘, ‘Popp‘, ‘LPOPP‘, ‘515.124.4567‘, ‘FI_ACCOUNT‘, ‘6900.00‘, null, ‘108‘, ‘100‘, ‘2000-09-09 00:00:00‘);
INSERT INTO employees VALUES (‘114‘, ‘Den‘, ‘Raphaely‘, ‘DRAPHEAL‘, ‘515.127.4561‘, ‘PU_MAN‘, ‘11000.00‘, null, ‘100‘, ‘30‘, ‘2000-09-09 00:00:00‘);
INSERT INTO employees VALUES (‘115‘, ‘Alexander‘, ‘Khoo‘, ‘AKHOO‘, ‘515.127.4562‘, ‘PU_CLERK‘, ‘3100.00‘, null, ‘114‘, ‘30‘, ‘2000-09-09 00:00:00‘);
INSERT INTO employees VALUES (‘116‘, ‘Shelli‘, ‘Baida‘, ‘SBAIDA‘, ‘515.127.4563‘, ‘PU_CLERK‘, ‘2900.00‘, null, ‘114‘, ‘30‘, ‘2000-09-09 00:00:00‘);
INSERT INTO employees VALUES (‘117‘, ‘Sigal‘, ‘Tobias‘, ‘STOBIAS‘, ‘515.127.4564‘, ‘PU_CLERK‘, ‘2800.00‘, null, ‘114‘, ‘30‘, ‘2000-09-09 00:00:00‘);
INSERT INTO employees VALUES (‘118‘, ‘Guy‘, ‘Himuro‘, ‘GHIMURO‘, ‘515.127.4565‘, ‘PU_CLERK‘, ‘2600.00‘, null, ‘114‘, ‘30‘, ‘2000-09-09 00:00:00‘);
INSERT INTO employees VALUES (‘119‘, ‘Karen‘, ‘Colmenares‘, ‘KCOLMENA‘, ‘515.127.4566‘, ‘PU_CLERK‘, ‘2500.00‘, null, ‘114‘, ‘30‘, ‘2000-09-09 00:00:00‘);
INSERT INTO employees VALUES (‘120‘, ‘Matthew‘, ‘Weiss‘, ‘MWEISS‘, ‘650.123.1234‘, ‘ST_MAN‘, ‘8000.00‘, null, ‘100‘, ‘50‘, ‘2004-02-06 00:00:00‘);
INSERT INTO employees VALUES (‘121‘, ‘Adam‘, ‘Fripp‘, ‘AFRIPP‘, ‘650.123.2234‘, ‘ST_MAN‘, ‘8200.00‘, null, ‘100‘, ‘50‘, ‘2004-02-06 00:00:00‘);
INSERT INTO employees VALUES (‘122‘, ‘Payam‘, ‘Kaufling‘, ‘PKAUFLIN‘, ‘650.123.3234‘, ‘ST_MAN‘, ‘7900.00‘, null, ‘100‘, ‘50‘, ‘2004-02-06 00:00:00‘);
INSERT INTO employees VALUES (‘123‘, ‘Shanta‘, ‘Vollman‘, ‘SVOLLMAN‘, ‘650.123.4234‘, ‘ST_MAN‘, ‘6500.00‘, null, ‘100‘, ‘50‘, ‘2004-02-06 00:00:00‘);
INSERT INTO employees VALUES (‘124‘, ‘Kevin‘, ‘Mourgos‘, ‘KMOURGOS‘, ‘650.123.5234‘, ‘ST_MAN‘, ‘5800.00‘, null, ‘100‘, ‘50‘, ‘2004-02-06 00:00:00‘);
INSERT INTO employees VALUES (‘125‘, ‘Julia‘, ‘Nayer‘, ‘JNAYER‘, ‘650.124.1214‘, ‘ST_CLERK‘, ‘3200.00‘, null, ‘120‘, ‘50‘, ‘2004-02-06 00:00:00‘);
INSERT INTO employees VALUES (‘126‘, ‘Irene‘, ‘Mikkilineni‘, ‘IMIKKILI‘, ‘650.124.1224‘, ‘ST_CLERK‘, ‘2700.00‘, null, ‘120‘, ‘50‘, ‘2004-02-06 00:00:00‘);
INSERT INTO employees VALUES (‘127‘, ‘James‘, ‘Landry‘, ‘JLANDRY‘, ‘650.124.1334‘, ‘ST_CLERK‘, ‘2400.00‘, null, ‘120‘, ‘50‘, ‘2004-02-06 00:00:00‘);
INSERT INTO employees VALUES (‘128‘, ‘Steven‘, ‘Markle‘, ‘SMARKLE‘, ‘650.124.1434‘, ‘ST_CLERK‘, ‘2200.00‘, null, ‘120‘, ‘50‘, ‘2004-02-06 00:00:00‘);
INSERT INTO employees VALUES (‘129‘, ‘Laura‘, ‘Bissot‘, ‘LBISSOT‘, ‘650.124.5234‘, ‘ST_CLERK‘, ‘3300.00‘, null, ‘121‘, ‘50‘, ‘2004-02-06 00:00:00‘);
INSERT INTO employees VALUES (‘130‘, ‘Mozhe‘, ‘Atkinson‘, ‘MATKINSO‘, ‘650.124.6234‘, ‘ST_CLERK‘, ‘2800.00‘, null, ‘121‘, ‘50‘, ‘2004-02-06 00:00:00‘);
INSERT INTO employees VALUES (‘131‘, ‘James‘, ‘Marlow‘, ‘JAMRLOW‘, ‘650.124.7234‘, ‘ST_CLERK‘, ‘2500.00‘, null, ‘121‘, ‘50‘, ‘2004-02-06 00:00:00‘);
INSERT INTO employees VALUES (‘132‘, ‘TJ‘, ‘Olson‘, ‘TJOLSON‘, ‘650.124.8234‘, ‘ST_CLERK‘, ‘2100.00‘, null, ‘121‘, ‘50‘, ‘2004-02-06 00:00:00‘);
INSERT INTO employees VALUES (‘133‘, ‘Jason‘, ‘Mallin‘, ‘JMALLIN‘, ‘650.127.1934‘, ‘ST_CLERK‘, ‘3300.00‘, null, ‘122‘, ‘50‘, ‘2004-02-06 00:00:00‘);
INSERT INTO employees VALUES (‘134‘, ‘Michael‘, ‘Rogers‘, ‘MROGERS‘, ‘650.127.1834‘, ‘ST_CLERK‘, ‘2900.00‘, null, ‘122‘, ‘50‘, ‘2002-12-23 00:00:00‘);
INSERT INTO employees VALUES (‘135‘, ‘Ki‘, ‘Gee‘, ‘KGEE‘, ‘650.127.1734‘, ‘ST_CLERK‘, ‘2400.00‘, null, ‘122‘, ‘50‘, ‘2002-12-23 00:00:00‘);
INSERT INTO employees VALUES (‘136‘, ‘Hazel‘, ‘Philtanker‘, ‘HPHILTAN‘, ‘650.127.1634‘, ‘ST_CLERK‘, ‘2200.00‘, null, ‘122‘, ‘50‘, ‘2002-12-23 00:00:00‘);
INSERT INTO employees VALUES (‘137‘, ‘Renske‘, ‘Ladwig‘, ‘RLADWIG‘, ‘650.121.1234‘, ‘ST_CLERK‘, ‘3600.00‘, null, ‘123‘, ‘50‘, ‘2002-12-23 00:00:00‘);
INSERT INTO employees VALUES (‘138‘, ‘Stephen‘, ‘Stiles‘, ‘SSTILES‘, ‘650.121.2034‘, ‘ST_CLERK‘, ‘3200.00‘, null, ‘123‘, ‘50‘, ‘2002-12-23 00:00:00‘);
INSERT INTO employees VALUES (‘139‘, ‘John‘, ‘Seo‘, ‘JSEO‘, ‘650.121.2019‘, ‘ST_CLERK‘, ‘2700.00‘, null, ‘123‘, ‘50‘, ‘2002-12-23 00:00:00‘);
INSERT INTO employees VALUES (‘140‘, ‘Joshua‘, ‘Patel‘, ‘JPATEL‘, ‘650.121.1834‘, ‘ST_CLERK‘, ‘2500.00‘, null, ‘123‘, ‘50‘, ‘2002-12-23 00:00:00‘);
INSERT INTO employees VALUES (‘171‘, ‘William‘, ‘Smith‘, ‘WSMITH‘, ‘011.44.1343.629268‘, ‘SA_REP‘, ‘7400.00‘, ‘0.15‘, ‘148‘, ‘80‘, ‘2014-03-05 00:00:00‘);
INSERT INTO employees VALUES (‘172‘, ‘Elizabeth‘, ‘Bates‘, ‘EBATES‘, ‘011.44.1343.529268‘, ‘SA_REP‘, ‘7300.00‘, ‘0.15‘, ‘148‘, ‘80‘, ‘2014-03-05 00:00:00‘);
INSERT INTO employees VALUES (‘173‘, ‘Sundita‘, ‘Kumar‘, ‘SKUMAR‘, ‘011.44.1343.329268‘, ‘SA_REP‘, ‘6100.00‘, ‘0.10‘, ‘148‘, ‘80‘, ‘2014-03-05 00:00:00‘);
INSERT INTO employees VALUES (‘201‘, ‘Michael‘, ‘Hartstein‘, ‘MHARTSTE‘, ‘515.123.5555‘, ‘MK_MAN‘, ‘13000.00‘, null, ‘100‘, ‘20‘, ‘2016-03-03 00:00:00‘);
INSERT INTO employees VALUES (‘202‘, ‘Pat‘, ‘Fay‘, ‘PFAY‘, ‘603.123.6666‘, ‘MK_REP‘, ‘6000.00‘, null, ‘201‘, ‘20‘, ‘2016-03-03 00:00:00‘);
INSERT INTO employees VALUES (‘203‘, ‘Susan‘, ‘Mavris‘, ‘SMAVRIS‘, ‘515.123.7777‘, ‘HR_REP‘, ‘6500.00‘, null, ‘101‘, ‘40‘, ‘2016-03-03 00:00:00‘);
INSERT INTO employees VALUES (‘204‘, ‘Hermann‘, ‘Baer‘, ‘HBAER‘, ‘515.123.8888‘, ‘PR_REP‘, ‘10000.00‘, null, ‘101‘, ‘70‘, ‘2016-03-03 00:00:00‘);
INSERT INTO employees VALUES (‘205‘, ‘Shelley‘, ‘Higgins‘, ‘SHIGGINS‘, ‘515.123.8080‘, ‘AC_MGR‘, ‘12000.00‘, null, ‘101‘, ‘110‘, ‘2016-03-03 00:00:00‘);
INSERT INTO employees VALUES (‘206‘, ‘William‘, ‘Gietz‘, ‘WGIETZ‘, ‘515.123.8181‘, ‘AC_ACCOUNT‘, ‘8300.00‘, null, ‘205‘, ‘110‘, ‘2016-03-03 00:00:00‘);

#jobs表
CREATE TABLE jobs (
  job_id varchar(10) NOT NULL,
  job_title varchar(35) DEFAULT NULL,
  min_salary int(6) DEFAULT NULL,
  max_salary int(6) DEFAULT NULL,
  PRIMARY KEY (job_id)
) ENGINE=InnoDB DEFAULT CHARSET=gb2312;
#jobs数据
INSERT INTO jobs VALUES (‘AC_ACCOUNT‘, ‘Public Accountant‘, ‘4200‘, ‘9000‘);
INSERT INTO jobs VALUES (‘AC_MGR‘, ‘Accounting Manager‘, ‘8200‘, ‘16000‘);
INSERT INTO jobs VALUES (‘AD_ASST‘, ‘Administration Assistant‘, ‘3000‘, ‘6000‘);
INSERT INTO jobs VALUES (‘AD_PRES‘, ‘President‘, ‘20000‘, ‘40000‘);
INSERT INTO jobs VALUES (‘AD_VP‘, ‘Administration Vice President‘, ‘15000‘, ‘30000‘);
INSERT INTO jobs VALUES (‘FI_ACCOUNT‘, ‘Accountant‘, ‘4200‘, ‘9000‘);
INSERT INTO jobs VALUES (‘FI_MGR‘, ‘Finance Manager‘, ‘8200‘, ‘16000‘);
INSERT INTO jobs VALUES (‘HR_REP‘, ‘Human Resources Representative‘, ‘4000‘, ‘9000‘);
INSERT INTO jobs VALUES (‘IT_PROG‘, ‘Programmer‘, ‘4000‘, ‘10000‘);
INSERT INTO jobs VALUES (‘MK_MAN‘, ‘Marketing Manager‘, ‘9000‘, ‘15000‘);
INSERT INTO jobs VALUES (‘MK_REP‘, ‘Marketing Representative‘, ‘4000‘, ‘9000‘);
INSERT INTO jobs VALUES (‘PR_REP‘, ‘Public Relations Representative‘, ‘4500‘, ‘10500‘);
INSERT INTO jobs VALUES (‘PU_CLERK‘, ‘Purchasing Clerk‘, ‘2500‘, ‘5500‘);
INSERT INTO jobs VALUES (‘PU_MAN‘, ‘Purchasing Manager‘, ‘8000‘, ‘15000‘);
INSERT INTO jobs VALUES (‘SA_MAN‘, ‘Sales Manager‘, ‘10000‘, ‘20000‘);
INSERT INTO jobs VALUES (‘SA_REP‘, ‘Sales Representative‘, ‘6000‘, ‘12000‘);
INSERT INTO jobs VALUES (‘SH_CLERK‘, ‘Shipping Clerk‘, ‘2500‘, ‘5500‘);
INSERT INTO jobs VALUES (‘ST_CLERK‘, ‘Stock Clerk‘, ‘2000‘, ‘5000‘);
INSERT INTO jobs VALUES (‘ST_MAN‘, ‘Stock Manager‘, ‘5500‘, ‘8500‘);

#locations表
CREATE TABLE locations (
  location_id int(11) NOT NULL AUTO_INCREMENT,
  street_address varchar(40) DEFAULT NULL,
  postal_code varchar(12) DEFAULT NULL,
  city varchar(30) DEFAULT NULL,
  state_province varchar(25) DEFAULT NULL,
  country_id varchar(2) DEFAULT NULL,
  PRIMARY KEY (location_id)
) ENGINE=InnoDB AUTO_INCREMENT=3201 DEFAULT CHARSET=gb2312;
#locations数据
INSERT INTO locations VALUES (‘1000‘, ‘1297 Via Cola di Rie‘, ‘00989‘, ‘Roma‘, null, ‘IT‘);
INSERT INTO locations VALUES (‘1100‘, ‘93091 Calle della Testa‘, ‘10934‘, ‘Venice‘, null, ‘IT‘);
INSERT INTO locations VALUES (‘1200‘, ‘2017 Shinjuku-ku‘, ‘1689‘, ‘Tokyo‘, ‘Tokyo Prefecture‘, ‘JP‘);
INSERT INTO locations VALUES (‘1300‘, ‘9450 Kamiya-cho‘, ‘6823‘, ‘Hiroshima‘, null, ‘JP‘);
INSERT INTO locations VALUES (‘1400‘, ‘2014 Jabberwocky Rd‘, ‘26192‘, ‘Southlake‘, ‘Texas‘, ‘US‘);
INSERT INTO locations VALUES (‘1500‘, ‘2011 Interiors Blvd‘, ‘99236‘, ‘South San Francisco‘, ‘California‘, ‘US‘);
INSERT INTO locations VALUES (‘1600‘, ‘2007 Zagora St‘, ‘50090‘, ‘South Brunswick‘, ‘New Jersey‘, ‘US‘);
INSERT INTO locations VALUES (‘1700‘, ‘2004 Charade Rd‘, ‘98199‘, ‘Seattle‘, ‘Washington‘, ‘US‘);
INSERT INTO locations VALUES (‘1800‘, ‘147 Spadina Ave‘, ‘M5V 2L7‘, ‘Toronto‘, ‘Ontario‘, ‘CA‘);
INSERT INTO locations VALUES (‘1900‘, ‘6092 Boxwood St‘, ‘YSW 9T2‘, ‘Whitehorse‘, ‘Yukon‘, ‘CA‘);
INSERT INTO locations VALUES (‘2000‘, ‘40-5-12 Laogianggen‘, ‘190518‘, ‘Beijing‘, null, ‘CN‘);
INSERT INTO locations VALUES (‘2100‘, ‘1298 Vileparle (E)‘, ‘490231‘, ‘Bombay‘, ‘Maharashtra‘, ‘IN‘);
INSERT INTO locations VALUES (‘2200‘, ‘12-98 Victoria Street‘, ‘2901‘, ‘Sydney‘, ‘New South Wales‘, ‘AU‘);
INSERT INTO locations VALUES (‘2300‘, ‘198 Clementi North‘, ‘540198‘, ‘Singapore‘, null, ‘SG‘);
INSERT INTO locations VALUES (‘2400‘, ‘8204 Arthur St‘, null, ‘London‘, null, ‘UK‘);
INSERT INTO locations VALUES (‘2500‘, ‘Magdalen Centre, The Oxford Science Park‘, ‘OX9 9ZB‘, ‘Oxford‘, ‘Oxford‘, ‘UK‘);
INSERT INTO locations VALUES (‘2600‘, ‘9702 Chester Road‘, ‘09629850293‘, ‘Stretford‘, ‘Manchester‘, ‘UK‘);
INSERT INTO locations VALUES (‘2700‘, ‘Schwanthalerstr. 7031‘, ‘80925‘, ‘Munich‘, ‘Bavaria‘, ‘DE‘);
INSERT INTO locations VALUES (‘2800‘, ‘Rua Frei Caneca 1360 ‘, ‘01307-002‘, ‘Sao Paulo‘, ‘Sao Paulo‘, ‘BR‘);
INSERT INTO locations VALUES (‘2900‘, ‘20 Rue des Corps-Saints‘, ‘1730‘, ‘Geneva‘, ‘Geneve‘, ‘CH‘);
INSERT INTO locations VALUES (‘3000‘, ‘Murtenstrasse 921‘, ‘3095‘, ‘Bern‘, ‘BE‘, ‘CH‘);
INSERT INTO locations VALUES (‘3100‘, ‘Pieter Breughelstraat 837‘, ‘3029SK‘, ‘Utrecht‘, ‘Utrecht‘, ‘NL‘);
INSERT INTO locations VALUES (‘3200‘, ‘Mariano Escobedo 9991‘, ‘11932‘, ‘Mexico City‘, ‘Distrito Federal,‘, ‘MX‘);