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MySQL之条件查询（DQL）

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标签：concat   ada   san   逻辑运算   选择   and   als   utf8   通配符   

条件查询

介绍：

　　根据条件过滤原始表的数据，查询到想要的数据。

语法：

　　select 要查询的字段|表达式|常量值|函数 from 表 where 条件;

WHERE

介绍：

　　使用WHERE子句，将不满足条件的行过滤掉，WHERE子句紧随FROM子句。

示例：

SELECT employee_id, last_name, job_id, department_id FROM employees WHERE department_id = 90 ;

比较运算

介绍：

　　=：等于

　　>：大于

　　>=：大于、等于

　　<：小于

　　<=：小于、等于

　　<>：不等于 (也可以是!=)

示例：

SELECT last_name, salary FROM employees WHERE salary <= 3000;

BETWEEN

介绍：

　　使用BETWEEN运算来显示在一个区间内的值。

特点：

　　1.使用between and可以提高语句的简洁度。

　　2.包含临界值。

　　3.两个临界值不要调换顺序。

示例：

SELECT last_name, salary FROM employees WHERE salary BETWEEN 2500 AND 3500;

IN

介绍：

　　判断某字段的值是否属于in列表中的某一项。

特点：

　　1.使用in提高语句简洁度。

　　2.in列表的值类型必须一致或兼容。

　　3.in列表中不支持通配符。

示例：

SELECT employee_id, last_name, salary, manager_id FROM employees WHERE manager_id IN (100, 101, 201);

LIKE

介绍：

　　1.使用LIKE运算选择类似的值。

　　2.一般和通配符搭配使用，选择条件可以包含字符或数字：

　　　　%代表零个或多个字符(任意个字符)

　　　　_代表一个字符

　　3.%和_可以同时使用。

示例：

SELECT first_name FROM employees WHERE first_name LIKE ‘S%‘;

SELECT last_name FROM employees WHERE last_name LIKE ‘_o%‘;

SELECT last_name FROM employees WHERE last_name LIKE CONCAT(‘%‘,‘o‘,‘%‘);

NULL

介绍：

　　=或<>不能用于判断null值，使用IS (NOT) NULL判断空值。

特点：

　　IS NULL：仅仅可以判断NULL值，可读性较高，建议使用。
　　安全等于<=>：既可以判断NULL值，又可以判断普通的数值，可读性较低。

示例：

SELECT last_name, manager_id FROM employees WHERE manager_id IS NULL;

逻辑运算AND

介绍（&&）：

　　逻辑并，两个条件如果同时成立，结果为true，否则为false。

示例：

SELECT employee_id, last_name, job_id, salary FROM employees WHERE salary >=10000 AND job_id LIKE ‘%MAN%‘;

逻辑运算OR

介绍（||）：

　　逻辑或，两个条件只要有一个成立，结果为true，否则为false。

示例：

SELECT employee_id, last_name, job_id, salary FROM employees WHERE salary >= 10000 OR job_id LIKE ‘%MAN%‘;

逻辑运算NOT

介绍：

　　逻辑否，如果条件成立，则not后为false，否则为true。

示例：

SELECT last_name, job_id FROM employees WHERE job_id NOT IN (‘IT_PROG‘, ‘ST_CLERK‘, ‘SA_REP‘);

案例讲解

#案例：查询工资>12000的员工信息
SELECT * FROM employees WHERE salary>12000;


#案例：查询部门编号不等于90号的员工名和部门编号
SELECT last_name,department_id FROM employees WHERE department_id<>90;


#案例：查询工资在10000到20000之间的员工名、工资以及奖金
SELECT last_name,salary,commission_pct FROM employees WHERE salary>=10000 AND salary<=20000;


#案例：查询部门编号不是在90到110之间，或者工资高于15000的员工信息
SELECT * FROM employees WHERE NOT(department_id>=90 AND  department_id<=110) OR salary>15000;


#案例：查询员工名中包含字符a的员工信息
SELECT * FROM employees WHERE last_name LIKE ‘%a%‘;


#案例：查询员工名中第三个字符为n，第五个字符为l的员工名和工资
SELECT last_name,salary FROM employees WHERE last_name LIKE ‘__n_l%‘;


#案例：查询员工名中第二个字符为_的员工名
SELECT last_name FROM employees WHERE last_name LIKE ‘_$_%‘ ESCAPE ‘$‘;


#案例：查询员工编号在100到120之间的员工信息
SELECT * FROM employees WHERE employee_id >= 100 AND employee_id<=120;
SELECT * FROM employees WHERE employee_id BETWEEN 100 AND 120;


#案例：查询员工的工种编号是IT_PROG、AD_VP、AD_PRES中的一个员工名和工种编号
SELECT last_name,job_id FROM employees WHERE job_id = ‘IT_PROT‘ OR job_id = ‘AD_VP‘ OR JOB_ID =‘AD_PRES‘;
SELECT last_name,job_id FROM employees WHERE job_id IN( ‘IT_PROT‘ ,‘AD_VP‘,‘AD_PRES‘);


#案例：查询没有奖金的员工名和奖金率
SELECT last_name,commission_pct FROM employees WHERE commission_pct IS NULL;


#案例：查询有奖金的员工名和奖金率
SELECT last_name,commission_pct FROM employees WHERE commission_pct IS NOT NULL;


#案例：查询没有奖金的员工名和奖金率
SELECT last_name,commission_pct FROM employees WHERE commission_pct <=>NULL;


#案例：查询工资为12000的员工信息
SELECT last_name,salary FROM employees WHERE salary <=> 12000;

测试数据

#员工表
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 DEFAULT CHARSET=utf8;

#员工数据
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‘);

MySQL之条件查询（DQL）

标签：concat   ada   san   逻辑运算   选择   and   als   utf8   通配符   

原文地址：https://www.cnblogs.com/hfl1996/p/13323968.html
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