1、准备数据源
/*
SQLyog Ultimate v10.00 Beta1
MySQL - 5.5.15 : Database - myemployees
*********************************************************************
*/
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/*!40014 SET @OLD_UNIQUE_CHECKS=@@UNIQUE_CHECKS, UNIQUE_CHECKS=0 */;
/*!40014 SET @OLD_FOREIGN_KEY_CHECKS=@@FOREIGN_KEY_CHECKS, FOREIGN_KEY_CHECKS=0 */;
/*!40101 SET @OLD_SQL_MODE=@@SQL_MODE, SQL_MODE='NO_AUTO_VALUE_ON_ZERO' */;
/*!40111 SET @OLD_SQL_NOTES=@@SQL_NOTES, SQL_NOTES=0 */;
CREATE DATABASE /*!32312 IF NOT EXISTS*/`myemployees` /*!40100 DEFAULT CHARACTER SET gb2312 */;
USE `myemployees`;
/*Table structure for table `departments` */
DROP TABLE IF EXISTS `departments`;
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;
/*Data for the table `departments` */
insert into `departments`(`department_id`,`department_name`,`manager_id`,`location_id`) values (10,'Adm',200,1700),(20,'Mar',201,1800),(30,'Pur',114,1700),(40,'Hum',203,2400),(50,'Shi',121,1500),(60,'IT',103,1400),(70,'Pub',204,2700),(80,'Sal',145,2500),(90,'Exe',100,1700),(100,'Fin',108,1700),(110,'Acc',205,1700),(120,'Tre',NULL,1700),(130,'Cor',NULL,1700),(140,'Con',NULL,1700),(150,'Sha',NULL,1700),(160,'Ben',NULL,1700),(170,'Man',NULL,1700),(180,'Con',NULL,1700),(190,'Con',NULL,1700),(200,'Ope',NULL,1700),(210,'IT ',NULL,1700),(220,'NOC',NULL,1700),(230,'IT ',NULL,1700),(240,'Gov',NULL,1700),(250,'Ret',NULL,1700),(260,'Rec',NULL,1700),(270,'Pay',NULL,1700);
/*Table structure for table `employees` */
DROP TABLE IF EXISTS `employees`;
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`),
KEY `dept_id_fk` (`department_id`),
KEY `job_id_fk` (`job_id`),
CONSTRAINT `dept_id_fk` FOREIGN KEY (`department_id`) REFERENCES `departments` (`department_id`),
CONSTRAINT `job_id_fk` FOREIGN KEY (`job_id`) REFERENCES `jobs` (`job_id`)
) ENGINE=InnoDB AUTO_INCREMENT=207 DEFAULT CHARSET=gb2312;
/*Data for the table `employees` */
insert into `employees`(`employee_id`,`first_name`,`last_name`,`email`,`phone_number`,`job_id`,`salary`,`commission_pct`,`manager_id`,`department_id`,`hiredate`) values (100,'Steven','K_ing','SKING','515.123.4567','AD_PRES',24000.00,NULL,NULL,90,'1992-04-03 00:00:00'),(101,'Neena','Kochhar','NKOCHHAR','515.123.4568','AD_VP',17000.00,NULL,100,90,'1992-04-03 00:00:00'),(102,'Lex','De Haan','LDEHAAN','515.123.4569','AD_VP',17000.00,NULL,100,90,'1992-04-03 00:00:00'),(103,'Alexander','Hunold','AHUNOLD','590.423.4567','IT_PROG',9000.00,NULL,102,60,'1992-04-03 00:00:00'),(104,'Bruce','Ernst','BERNST','590.423.4568','IT_PROG',6000.00,NULL,103,60,'1992-04-03 00:00:00'),(105,'David','Austin','DAUSTIN','590.423.4569','IT_PROG',4800.00,NULL,103,60,'1998-03-03 00:00:00'),(106,'Valli','Pataballa','VPATABAL','590.423.4560','IT_PROG',4800.00,NULL,103,60,'1998-03-03 00:00:00'),(107,'Diana','Lorentz','DLORENTZ','590.423.5567','IT_PROG',4200.00,NULL,103,60,'1998-03-03 00:00:00'),(108,'Nancy','Greenberg','NGREENBE','515.124.4569','FI_MGR',12000.00,NULL,101,100,'1998-03-03 00:00:00'),(109,'Daniel','Faviet','DFAVIET','515.124.4169','FI_ACCOUNT',9000.00,NULL,108,100,'1998-03-03 00:00:00'),(110,'John','Chen','JCHEN','515.124.4269','FI_ACCOUNT',8200.00,NULL,108,100,'2000-09-09 00:00:00'),(111,'Ismael','Sciarra','ISCIARRA','515.124.4369','FI_ACCOUNT',7700.00,NULL,108,100,'2000-09-09 00:00:00'),(112,'Jose Manuel','Urman','JMURMAN','515.124.4469','FI_ACCOUNT',7800.00,NULL,108,100,'2000-09-09 00:00:00'),(113,'Luis','Popp','LPOPP','515.124.4567','FI_ACCOUNT',6900.00,NULL,108,100,'2000-09-09 00:00:00'),(114,'Den','Raphaely','DRAPHEAL','515.127.4561','PU_MAN',11000.00,NULL,100,30,'2000-09-09 00:00:00'),(115,'Alexander','Khoo','AKHOO','515.127.4562','PU_CLERK',3100.00,NULL,114,30,'2000-09-09 00:00:00'),(116,'Shelli','Baida','SBAIDA','515.127.4563','PU_CLERK',2900.00,NULL,114,30,'2000-09-09 00:00:00'),(117,'Sigal','Tobias','STOBIAS','515.127.4564','PU_CLERK',2800.00,NULL,114,30,'2000-09-09 00:00:00'),(118,'Guy','Himuro','GHIMURO','515.127.4565','PU_CLERK',2600.00,NULL,114,30,'2000-09-09 00:00:00'),(119,'Karen','Colmenares','KCOLMENA','515.127.4566','PU_CLERK',2500.00,NULL,114,30,'2000-09-09 00:00:00'),(120,'Matthew','Weiss','MWEISS','650.123.1234','ST_MAN',8000.00,NULL,100,50,'2004-02-06 00:00:00'),(121,'Adam','Fripp','AFRIPP','650.123.2234','ST_MAN',8200.00,NULL,100,50,'2004-02-06 00:00:00'),(122,'Payam','Kaufling','PKAUFLIN','650.123.3234','ST_MAN',7900.00,NULL,100,50,'2004-02-06 00:00:00'),(123,'Shanta','Vollman','SVOLLMAN','650.123.4234','ST_MAN',6500.00,NULL,100,50,'2004-02-06 00:00:00'),(124,'Kevin','Mourgos','KMOURGOS','650.123.5234','ST_MAN',5800.00,NULL,100,50,'2004-02-06 00:00:00'),(125,'Julia','Nayer','JNAYER','650.124.1214','ST_CLERK',3200.00,NULL,120,50,'2004-02-06 00:00:00'),(126,'Irene','Mikkilineni','IMIKKILI','650.124.1224','ST_CLERK',2700.00,NULL,120,50,'2004-02-06 00:00:00'),(127,'James','Landry','JLANDRY','650.124.1334','ST_CLERK',2400.00,NULL,120,50,'2004-02-06 00:00:00'),(128,'Steven','Markle','SMARKLE','650.124.1434','ST_CLERK',2200.00,NULL,120,50,'2004-02-06 00:00:00'),(129,'Laura','Bissot','LBISSOT','650.124.5234','ST_CLERK',3300.00,NULL,121,50,'2004-02-06 00:00:00'),(130,'Mozhe','Atkinson','MATKINSO','650.124.6234','ST_CLERK',2800.00,NULL,121,50,'2004-02-06 00:00:00'),(131,'James','Marlow','JAMRLOW','650.124.7234','ST_CLERK',2500.00,NULL,121,50,'2004-02-06 00:00:00'),(132,'TJ','Olson','TJOLSON','650.124.8234','ST_CLERK',2100.00,NULL,121,50,'2004-02-06 00:00:00'),(133,'Jason','Mallin','JMALLIN','650.127.1934','ST_CLERK',3300.00,NULL,122,50,'2004-02-06 00:00:00'),(134,'Michael','Rogers','MROGERS','650.127.1834','ST_CLERK',2900.00,NULL,122,50,'2002-12-23 00:00:00'),(135,'Ki','Gee','KGEE','650.127.1734','ST_CLERK',2400.00,NULL,122,50,'2002-12-23 00:00:00'),(136,'Hazel','Philtanker','HPHILTAN','650.127.1634','ST_CLERK',2200.00,NULL,122,50,'2002-12-23 00:00:00'),(137,'Renske','Ladwig','RLADWIG','650.121.1234','ST_CLERK',3600.00,NULL,123,50,'2002-12-23 00:00:00'),(138,'Stephen','Stiles','SSTILES','650.121.2034','ST_CLERK',3200.00,NULL,123,50,'2002-12-23 00:00:00'),(139,'John','Seo','JSEO','650.121.2019','ST_CLERK',2700.00,NULL,123,50,'2002-12-23 00:00:00'),(140,'Joshua','Patel','JPATEL','650.121.1834','ST_CLERK',2500.00,NULL,123,50,'2002-12-23 00:00:00'),(141,'Trenna','Rajs','TRAJS','650.121.8009','ST_CLERK',3500.00,NULL,124,50,'2002-12-23 00:00:00'),(142,'Curtis','Davies','CDAVIES','650.121.2994','ST_CLERK',3100.00,NULL,124,50,'2002-12-23 00:00:00'),(143,'Randall','Matos','RMATOS','650.121.2874','ST_CLERK',2600.00,NULL,124,50,'2002-12-23 00:00:00'),(144,'Peter','Vargas','PVARGAS','650.121.2004','ST_CLERK',2500.00,NULL,124,50,'2002-12-23 00:00:00'),(145,'John','Russell','JRUSSEL','011.44.1344.429268','SA_MAN',14000.00,0.40,100,80,'2002-12-23 00:00:00'),(146,'Karen','Partners','KPARTNER','011.44.1344.467268','SA_MAN',13500.00,0.30,100,80,'2002-12-23 00:00:00'),(147,'Alberto','Errazuriz','AERRAZUR','011.44.1344.429278','SA_MAN',12000.00,0.30,100,80,'2002-12-23 00:00:00'),(148,'Gerald','Cambrault','GCAMBRAU','011.44.1344.619268','SA_MAN',11000.00,0.30,100,80,'2002-12-23 00:00:00'),(149,'Eleni','Zlotkey','EZLOTKEY','011.44.1344.429018','SA_MAN',10500.00,0.20,100,80,'2002-12-23 00:00:00'),(150,'Peter','Tucker','PTUCKER','011.44.1344.129268','SA_REP',10000.00,0.30,145,80,'2014-03-05 00:00:00'),(151,'David','Bernstein','DBERNSTE','011.44.1344.345268','SA_REP',9500.00,0.25,145,80,'2014-03-05 00:00:00'),(152,'Peter','Hall','PHALL','011.44.1344.478968','SA_REP',9000.00,0.25,145,80,'2014-03-05 00:00:00'),(153,'Christopher','Olsen','COLSEN','011.44.1344.498718','SA_REP',8000.00,0.20,145,80,'2014-03-05 00:00:00'),(154,'Nanette','Cambrault','NCAMBRAU','011.44.1344.987668','SA_REP',7500.00,0.20,145,80,'2014-03-05 00:00:00'),(155,'Oliver','Tuvault','OTUVAULT','011.44.1344.486508','SA_REP',7000.00,0.15,145,80,'2014-03-05 00:00:00'),(156,'Janette','K_ing','JKING','011.44.1345.429268','SA_REP',10000.00,0.35,146,80,'2014-03-05 00:00:00'),(157,'Patrick','Sully','PSULLY','011.44.1345.929268','SA_REP',9500.00,0.35,146,80,'2014-03-05 00:00:00'),(158,'Allan','McEwen','AMCEWEN','011.44.1345.829268','SA_REP',9000.00,0.35,146,80,'2014-03-05 00:00:00'),(159,'Lindsey','Smith','LSMITH','011.44.1345.729268','SA_REP',8000.00,0.30,146,80,'2014-03-05 00:00:00'),(160,'Louise','Doran','LDORAN','011.44.1345.629268','SA_REP',7500.00,0.30,146,80,'2014-03-05 00:00:00'),(161,'Sarath','Sewall','SSEWALL','011.44.1345.529268','SA_REP',7000.00,0.25,146,80,'2014-03-05 00:00:00'),(162,'Clara','Vishney','CVISHNEY','011.44.1346.129268','SA_REP',10500.00,0.25,147,80,'2014-03-05 00:00:00'),(163,'Danielle','Greene','DGREENE','011.44.1346.229268','SA_REP',9500.00,0.15,147,80,'2014-03-05 00:00:00'),(164,'Mattea','Marvins','MMARVINS','011.44.1346.329268','SA_REP',7200.00,0.10,147,80,'2014-03-05 00:00:00'),(165,'David','Lee','DLEE','011.44.1346.529268','SA_REP',6800.00,0.10,147,80,'2014-03-05 00:00:00'),(166,'Sundar','Ande','SANDE','011.44.1346.629268','SA_REP',6400.00,0.10,147,80,'2014-03-05 00:00:00'),(167,'Amit','Banda','ABANDA','011.44.1346.729268','SA_REP',6200.00,0.10,147,80,'2014-03-05 00:00:00'),(168,'Lisa','Ozer','LOZER','011.44.1343.929268','SA_REP',11500.00,0.25,148,80,'2014-03-05 00:00:00'),(169,'Harrison','Bloom','HBLOOM','011.44.1343.829268','SA_REP',10000.00,0.20,148,80,'2014-03-05 00:00:00'),(170,'Tayler','Fox','TFOX','011.44.1343.729268','SA_REP',9600.00,0.20,148,80,'2014-03-05 00:00:00'),(171,'William','Smith','WSMITH','011.44.1343.629268','SA_REP',7400.00,0.15,148,80,'2014-03-05 00:00:00'),(172,'Elizabeth','Bates','EBATES','011.44.1343.529268','SA_REP',7300.00,0.15,148,80,'2014-03-05 00:00:00'),(173,'Sundita','Kumar','SKUMAR','011.44.1343.329268','SA_REP',6100.00,0.10,148,80,'2014-03-05 00:00:00'),(174,'Ellen','Abel','EABEL','011.44.1644.429267','SA_REP',11000.00,0.30,149,80,'2014-03-05 00:00:00'),(175,'Alyssa','Hutton','AHUTTON','011.44.1644.429266','SA_REP',8800.00,0.25,149,80,'2014-03-05 00:00:00'),(176,'Jonathon','Taylor','JTAYLOR','011.44.1644.429265','SA_REP',8600.00,0.20,149,80,'2014-03-05 00:00:00'),(177,'Jack','Livingston','JLIVINGS','011.44.1644.429264','SA_REP',8400.00,0.20,149,80,'2014-03-05 00:00:00'),(178,'Kimberely','Grant','KGRANT','011.44.1644.429263','SA_REP',7000.00,0.15,149,NULL,'2014-03-05 00:00:00'),(179,'Charles','Johnson','CJOHNSON','011.44.1644.429262','SA_REP',6200.00,0.10,149,80,'2014-03-05 00:00:00'),(180,'Winston','Taylor','WTAYLOR','650.507.9876','SH_CLERK',3200.00,NULL,120,50,'2014-03-05 00:00:00'),(181,'Jean','Fleaur','JFLEAUR','650.507.9877','SH_CLERK',3100.00,NULL,120,50,'2014-03-05 00:00:00'),(182,'Martha','Sullivan','MSULLIVA','650.507.9878','SH_CLERK',2500.00,NULL,120,50,'2014-03-05 00:00:00'),(183,'Girard','Geoni','GGEONI','650.507.9879','SH_CLERK',2800.00,NULL,120,50,'2014-03-05 00:00:00'),(184,'Nandita','Sarchand','NSARCHAN','650.509.1876','SH_CLERK',4200.00,NULL,121,50,'2014-03-05 00:00:00'),(185,'Alexis','Bull','ABULL','650.509.2876','SH_CLERK',4100.00,NULL,121,50,'2014-03-05 00:00:00'),(186,'Julia','Dellinger','JDELLING','650.509.3876','SH_CLERK',3400.00,NULL,121,50,'2014-03-05 00:00:00'),(187,'Anthony','Cabrio','ACABRIO','650.509.4876','SH_CLERK',3000.00,NULL,121,50,'2014-03-05 00:00:00'),(188,'Kelly','Chung','KCHUNG','650.505.1876','SH_CLERK',3800.00,NULL,122,50,'2014-03-05 00:00:00'),(189,'Jennifer','Dilly','JDILLY','650.505.2876','SH_CLERK',3600.00,NULL,122,50,'2014-03-05 00:00:00'),(190,'Timothy','Gates','TGATES','650.505.3876','SH_CLERK',2900.00,NULL,122,50,'2014-03-05 00:00:00'),(191,'Randall','Perkins','RPERKINS','650.505.4876','SH_CLERK',2500.00,NULL,122,50,'2014-03-05 00:00:00'),(192,'Sarah','Bell','SBELL','650.501.1876','SH_CLERK',4000.00,NULL,123,50,'2014-03-05 00:00:00'),(193,'Britney','Everett','BEVERETT','650.501.2876','SH_CLERK',3900.00,NULL,123,50,'2014-03-05 00:00:00'),(194,'Samuel','McCain','SMCCAIN','650.501.3876','SH_CLERK',3200.00,NULL,123,50,'2014-03-05 00:00:00'),(195,'Vance','Jones','VJONES','650.501.4876','SH_CLERK',2800.00,NULL,123,50,'2014-03-05 00:00:00'),(196,'Alana','Walsh','AWALSH','650.507.9811','SH_CLERK',3100.00,NULL,124,50,'2014-03-05 00:00:00'),(197,'Kevin','Feeney','KFEENEY','650.507.9822','SH_CLERK',3000.00,NULL,124,50,'2014-03-05 00:00:00'),(198,'Donald','OConnell','DOCONNEL','650.507.9833','SH_CLERK',2600.00,NULL,124,50,'2014-03-05 00:00:00'),(199,'Douglas','Grant','DGRANT','650.507.9844','SH_CLERK',2600.00,NULL,124,50,'2014-03-05 00:00:00'),(200,'Jennifer','Whalen','JWHALEN','515.123.4444','AD_ASST',4400.00,NULL,101,10,'2016-03-03 00:00:00'),(201,'Michael','Hartstein','MHARTSTE','515.123.5555','MK_MAN',13000.00,NULL,100,20,'2016-03-03 00:00:00'),(202,'Pat','Fay','PFAY','603.123.6666','MK_REP',6000.00,NULL,201,20,'2016-03-03 00:00:00'),(203,'Susan','Mavris','SMAVRIS','515.123.7777','HR_REP',6500.00,NULL,101,40,'2016-03-03 00:00:00'),(204,'Hermann','Baer','HBAER','515.123.8888','PR_REP',10000.00,NULL,101,70,'2016-03-03 00:00:00'),(205,'Shelley','Higgins','SHIGGINS','515.123.8080','AC_MGR',12000.00,NULL,101,110,'2016-03-03 00:00:00'),(206,'William','Gietz','WGIETZ','515.123.8181','AC_ACCOUNT',8300.00,NULL,205,110,'2016-03-03 00:00:00');
/*Table structure for table `jobs` */
DROP TABLE IF EXISTS `jobs`;
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;
/*Data for the table `jobs` */
insert into `jobs`(`job_id`,`job_title`,`min_salary`,`max_salary`) values ('AC_ACCOUNT','Public Accountant',4200,9000),('AC_MGR','Accounting Manager',8200,16000),('AD_ASST','Administration Assistant',3000,6000),('AD_PRES','President',20000,40000),('AD_VP','Administration Vice President',15000,30000),('FI_ACCOUNT','Accountant',4200,9000),('FI_MGR','Finance Manager',8200,16000),('HR_REP','Human Resources Representative',4000,9000),('IT_PROG','Programmer',4000,10000),('MK_MAN','Marketing Manager',9000,15000),('MK_REP','Marketing Representative',4000,9000),('PR_REP','Public Relations Representative',4500,10500),('PU_CLERK','Purchasing Clerk',2500,5500),('PU_MAN','Purchasing Manager',8000,15000),('SA_MAN','Sales Manager',10000,20000),('SA_REP','Sales Representative',6000,12000),('SH_CLERK','Shipping Clerk',2500,5500),('ST_CLERK','Stock Clerk',2000,5000),('ST_MAN','Stock Manager',5500,8500);
/*Table structure for table `locations` */
DROP TABLE IF EXISTS `locations`;
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;
/*Data for the table `locations` */
insert into `locations`(`location_id`,`street_address`,`postal_code`,`city`,`state_province`,`country_id`) values (1000,'1297 Via Cola di Rie','00989','Roma',NULL,'IT'),(1100,'93091 Calle della Testa','10934','Venice',NULL,'IT'),(1200,'2017 Shinjuku-ku','1689','Tokyo','Tokyo Prefecture','JP'),(1300,'9450 Kamiya-cho','6823','Hiroshima',NULL,'JP'),(1400,'2014 Jabberwocky Rd','26192','Southlake','Texas','US'),(1500,'2011 Interiors Blvd','99236','South San Francisco','California','US'),(1600,'2007 Zagora St','50090','South Brunswick','New Jersey','US'),(1700,'2004 Charade Rd','98199','Seattle','Washington','US'),(1800,'147 Spadina Ave','M5V 2L7','Toronto','Ontario','CA'),(1900,'6092 Boxwood St','YSW 9T2','Whitehorse','Yukon','CA'),(2000,'40-5-12 Laogianggen','190518','Beijing',NULL,'CN'),(2100,'1298 Vileparle (E)','490231','Bombay','Maharashtra','IN'),(2200,'12-98 Victoria Street','2901','Sydney','New South Wales','AU'),(2300,'198 Clementi North','540198','Singapore',NULL,'SG'),(2400,'8204 Arthur St',NULL,'London',NULL,'UK'),(2500,'Magdalen Centre, The Oxford Science Park','OX9 9ZB','Oxford','Oxford','UK'),(2600,'9702 Chester Road','09629850293','Stretford','Manchester','UK'),(2700,'Schwanthalerstr. 7031','80925','Munich','Bavaria','DE'),(2800,'Rua Frei Caneca 1360 ','01307-002','Sao Paulo','Sao Paulo','BR'),(2900,'20 Rue des Corps-Saints','1730','Geneva','Geneve','CH'),(3000,'Murtenstrasse 921','3095','Bern','BE','CH'),(3100,'Pieter Breughelstraat 837','3029SK','Utrecht','Utrecht','NL'),(3200,'Mariano Escobedo 9991','11932','Mexico City','Distrito Federal,','MX');
CREATE TABLE job_grades
(grade_level VARCHAR(3),
lowest_sal INT,
highest_sal INT);
INSERT INTO job_grades
VALUES ('A', 1000, 2999);
INSERT INTO job_grades
VALUES ('B', 3000, 5999);
INSERT INTO job_grades
VALUES('C', 6000, 9999);
INSERT INTO job_grades
VALUES('D', 10000, 14999);
INSERT INTO job_grades
VALUES('E', 15000, 24999);
INSERT INTO job_grades
VALUES('F', 25000, 40000);
2、基础查询
类似system.out.print("打印东西");
特点:
a. 查询列表可以是:表中的字段、常量值、表达式、函数
b. 查询的结果可以是一个虚拟表格。
USE myemployees;
#1.查询表中的单个字段
SELECT last_name FROM employees;
#2.查询表中多个字段
SELECT last_name,salary,email FROM employees;
#3.查询表中的所有字段
SELECT * FROM employees;
#4.查询常量
# select 常量值;
# 注意:字符型和日期型的常量值必须用单引号引起来,数值型不需要
SELECT 100;
SELECT 'join';
#5.查询函数
#select 函数名(实参列表);
SELECT VERSION();
#6.查询表达式
SELECT 100%98;
#7.起别名
/*
1.便于理解
2.如果要查询的字段有重名的情况,使用别名区分
*/
#方式一:使用AS
SELECT 100%98 AS 结果;
SELECT last_name AS 姓,first_name AS 名 FROM employees;
#方式二:使用空格
SELECT last_name 姓,first_name 名 FROM employees;
#案例:查询salary,结果显示 out put
SELECT salary AS "out put" FROM employees;
#8.去重
# select distinct 字段名 from 表名;
#案例:查询员工表中涉及的所有部门编号
SELECT DISTINCT department_id FROM employees;
#9.+号的作用
#案例:查询员工的名和姓,并显示为姓名
/*
java中的+号:
1.运算符:两个操作数都为数据型
2.连接符:只要有一个操作数为字符串
mysql中的+号:
只能作为运算符
select 100+90; 两个操作数都为数值型,做加法运算
select '123+90';其中一方为字符型,试图将字符型数值转换为数值型
如果转换成功,则继续做加法运算
select 'john'+90; 如果转换失败,则将字符型数值转换成0
select null+0; 只要其中一方为null,则结果肯定为null.
*/
SELECT last_name+first_name AS 姓名 FROM employees;
#10.【补充】concat函数
/*
功能:拼接字符
select concat(字符1,字符2,字符3,...);
*/
SELECT CONCAT('a','b','c') AS 结果 FROM employees;
SELECT CONCAT(last_name,first_name) AS 姓名 FROM employees;
#11.【补充】ifnull函数
#功能:判断某字段或表达式是否为null,如果为null 返回指定的值,否则返回原本的值
SELECT IFNULL(commission_pct,0) FROM employees;
#12.【补充】isnull函数
#功能:判断某字段或表达式是否为null,如果是,则返回1,否则返回0
3、条件查询
- 1、按条件表达式筛选
- 条件运算符:> < = != <> >= <= <=>安全等于
- 2、按逻辑表达式筛选
- 逻辑运算符:&& || |
- and or not
- && 和 and:两个条件都为true,结果为true,反之为false
- || 和 or:只要有一个条件为true,结果为true,反之为false
- ! 或 not:如果连接的条件本身为false,结果为true,反之为false
- 3、模糊查询
- like:一般搭配通配符使用,可以判断字符型或数值型
- 通配符:%任意多个字符,_任意单个字符
- like、between and、in、is null
实例
#一.按条件表达式筛选
#案例1:查询工资>12000的员工信息
SELECT * FROM employees WHERE salary>12000;
#案例2: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;
#二、按逻辑表达式筛选
#案例1:查询工资z在10000到20000之间的员工名、工资及奖金
SELECT last_name,salary,commission_pct FROM employees WHERE salary>=10000 AND salary<=20000;
#案例2:查询部门编号不是在90-110之间,或者工资高于15000的员工信息
SELECT * FROM employees WHERE department_id <90 OR department_id>110 OR salary>15000;
#三、模糊查询
#1.like
#案例1: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2:查询员工名中第三个字符为b,第五个字符为a的员工名和工资
SELECT last_name,salary FROM employees WHERE last_name LIKE '__b_a%';
#案例3:查询员工名种第二个字符为_的员工名
SELECT last_name FROM employees WHERE last_name LIKE '_\_%';
#2.between and
#案例1: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;
/*注意事项:
1.提高语句简洁度
2.包含临界值
3.两个临界值不能调换顺序
*/
#3.in
/*
含义: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
*/
#案例1: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_PROG' OR job_id='AD_PRES' OR job_id='AD_VP';
SELECT last_name,job_id FROM employees WHERE job_id IN('IT_PROG','AD_PRES','AD_VP');
#4.is null
/*
=或<>不能用于判断null值
is null 或 is not null 可以判断null值
*/
#案例1: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;
SELECT last_name,commission_pct FROM employees WHERE commission_pct IS NOT NULL;
#安全等于<=>
#案例1: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2:查询工资为12000的员工信息
SELECT last_name,commission_pct FROM employees WHERE salary <=> 12000;
#is null PK <=>
# 普通类型的数值 null值 可读性
# is null × √ √
# <=> √ √ ×
4、排序查询
- 1.asc代表的是升序,desc代表降序,不写默认为升序
- 2.order by子句中可以支持单个字段、多个字段、表达式、函数、别名
- 3.order by子句一般是放在查询语句的最后面,limit子句除外
#案例1:查询员工信息,要求工资从高到低排序
SELECT * FROM employees ORDER BY salary DESC;
SELECT * FROM employees ORDER BY salary;
#案例2:查询部门编号是>=90,按入职时间的先后进行排序
SELECT * FROM employees WHERE department_id>=90 ORDER BY hiredate ASC;
#案例3:按年薪的高低显示员工的信息和年薪【按表达式排序】
SELECT *,salary*12*(1+IFNULL(commission_pct,0)) 年薪 FROM employees
ORDER BY salary*12*(1+IFNULL(commission_pct,0)) DESC;
#案例4:按年薪的高低显示员工的信息和年薪【按别名排序】 这里5.6版本好像不支持
SELECT *,salary*12*(1+IFNULL(commission_pct,0)) 年薪 FROM employees
ORDER BY salary*12*(1+IFNULL(commission_pct,0)) 年薪DESC;
#案例5:按姓名的长度显示员工的姓名和工资【按函数排序】
SELECT LENGTH(last_name) 字节长度,last_name,salary
FROM employees
ORDER BY LENGTH(last_name) DESC;
#案例6:查询员工共信息,要求按工资排序,再按员工编号排序【按多个字段排序】
SELECT * FROM employees
ORDER BY salary ASC,employee_id DESC;
5、常见函数
单行函数
- 单行函数分类:字符函数、数学函数、日期函数、其他函数、流程控制函数
字符函数具体案例:
#一.字符函数
#1.length 获取参数值的字节值
SELECT LENGTH('subei');
SELECT LENGTH('鬼谷子qwe');
SHOW VARIABLES LIKE '%char%';
#2.concat 拼接字符串
SELECT CONCAT(last_name,'_',first_name) 姓名 FROM employees;
#3.upper:变大写、lower:变小写
SELECT UPPER('ton');
SELECT LOWER('ton');
#示例:将姓变大写,名变小写,然后拼接
SELECT CONCAT(UPPER(last_name),LOWER(first_name)) 姓名 FROM employees;
#4.substr、substring
#注意:索引从1开始
#截取从指定所有处后面的所以字符
SELECT SUBSTR('吴刚伐桂在天上',4) out_put;
#截取从指定索引处指定字符长度的字符
SELECT SUBSTR('吴刚伐桂在天上',1,2) out_put;
#案例:姓名中首字符大写,其他字符小写,然后用_拼接,显示出来
SELECT CONCAT(UPPER(SUBSTR(last_name,1,1)),'_',LOWER(SUBSTR(last_name,2))) out_put FROM employees;
#5.instr:获取子串第一次出现的索引,找不到返回0
SELECT INSTR('MySQL技术进阶','技术') AS out_put;
#6.trim:去前后空格
SELECT LENGTH(TRIM(' 霍山 ')) AS out_put;
SELECT TRIM('+' FROM '++++李刚+++刘邦+++') AS out_put;
#7.lpad:用指定的字符实现左填充指定长度
SELECT LPAD('梅林',8,'+') AS out_put;
#8.rpad:用指定的字符实现右填充指定长度
SELECT RPAD('梅林',5,'&') AS out_put;
#9.replace:替换
SELECT REPLACE('莉莉伊万斯的青梅竹马是詹姆','詹姆','斯内普') AS out_put;
数学函数具体案例:
#1.round:四舍五入
SELECT ROUND(1.45);
SELECT ROUND(1.567,2);
#2.ceil:向上取整,返回>=该参数的最小整数
SELECT CEIL(1.005);
SELECT CEIL(-1.002);
#3.floor:向下取整,返回<=该参数的最大整数
SELECT FLOOR(-9.99);
#4.truncate:截断
SELECT TRUNCATE(1.65,1);
#5.mod:取余
SELECT MOD(10,3);
#6.rand:获取随机数,返回0-1之间的小数
SELECT RAND();
日期函数具体案例:
#1.now:返回当前系统时间+日期
SELECT NOW();
#2.year:返回年
SELECT YEAR(NOW());
SELECT YEAR(hiredate) 年 FROM employees;
#3.month:返回月
#MONTHNAME:以英文形式返回月
SELECT MONTH(NOW());
SELECT MONTHNAME(NOW());
#4.day:返回日
#DATEDIFF:返回两个日期相差的天数
SELECT DAY(NOW());
SELECT DATEDIFF('2020/06/30','2020/06/21');
#5.str_to_date:将字符通过指定格式转换成日期
SELECT STR_TO_DATE('2020-5-13','%Y-%c-%d') AS out_put;
#6.date_format:将日期转换成字符
SELECT DATE_FORMAT('2020/6/6','%Y年%m月%d日') AS out_put;
SELECT DATE_FORMAT(NOW(),'%Y年%m月%d日') AS out_put;
#7.curdate:返回当前日期
SELECT CURDATE();
#8.curtime:返回当前时间
SELECT CURTIME();
其他函数具体案例:
#version 当前数据库服务器的版本
SELECT VERSION();
#database 当前打开的数据库
SELECT DATABASE();
#user当前用户
SELECT USER();
#password('字符'):返回该字符的密码形式
SELECT PASSWORD('a');
#md5('字符'):返回该字符的md5加密形式
SELECT MD5('a');
流程控制函数具体案例:
#1.if函数: if else效果
SELECT IF(10<5,'大','小');
SELECT last_name,commission_pct,IF(commission_pct IS NULL,'没奖金!!!','有奖金!!!') 备注 FROM employees;
#2.case函数
#使用一:switch case 的效果
/*
java中
switch(变量或表达式){
case 常量1:语句1;break;
...
default:语句n;break;
}
mysql中
case 要判断的变量或表达式
when 常量1 then 要显示的值1或语句1
when 常量2 then 要显示的值2或语句2
...
else 要显示的值n或语句n
end
#案例:查询员工的工资,要求:
部门号=30,显示的工资为1.1倍
部门号=40,显示的工资为1.2倍
部门号=50,显示的工资为1.3倍
其他部门,显示的工资为原工资
*/
SELECT salary 原始工资,department_id,
CASE department_id
WHEN 30 THEN salary*1.1
WHEN 40 THEN salary*1.2
WHEN 50 THEN salary*1.3
ELSE salary
END AS 新工资
FROM employees;
#3.case函数的使用二:类似于多重if
/*
java中:
if(条件1){
语句1;
}else if(条件2){
语句2;
}
...
else{
语句n;
}
mysql中:
case
when 条件1 then 要显示的值1或语句1
when 条件2 then 要显示的值2或语句2
...
else 要显示的值n或语句n
end
*/
#案例:查询员工的工资的情况
/*
如果工资>20000,显示A级别
如果工资>15000,显示B级别
如果工资>10000,显示c级别
否则,显示D级别
*/
SELECT salary,
CASE
WHEN salary>20000 THEN 'A'
WHEN salary>15000 THEN 'B'
WHEN salary>10000 THEN 'C'
ELSE 'D'
END AS 工资等级
FROM employees;
分组函数
- 功能:用作统计使用,又称为聚合函数或统计函数或组函数
- 分类:sum 求和、avg 平均值、max 最大值、min最小值count 计算个数
- 特点:
- 1.sum和avg一般用于处理数值型
max、min、count可以处理任何数据类型 - 2.以上分组函数都忽略null
- 3.都可以搭配distinct使用,实现去重的统计
select sum(distinct 字段) from 表; - 4.count函数
count(字段):统计该字段非空值的个数
count(*):统计结果集的行数 - 5.和分组函数一同查询的字段,要求是group by后出现的字段
#1.简单使用
SELECT SUM(salary) FROM employees;
SELECT AVG(salary) FROM employees;
SELECT MAX(salary) FROM employees;
SELECT MIN(salary) FROM employees;
SELECT COUNT(salary) FROM employees;
SELECT SUM(salary) 和,ROUND(AVG(salary),2) 平均,MAX(salary) 最高,MIN(salary) 最低,COUNT(salary) 个数
FROM employees;
#2.参数支持哪些数据类型
SELECT SUM(last_name),AVG(last_name) FROM employees;
SELECT SUM(hiredate),AVG(hiredate) FROM employees;
SELECT MAX(last_name),MIN(last_name) FROM employees;
SELECT MAX(hiredate),MIN(hiredate) FROM employees;
SELECT COUNT(commission_pct) FROM employees;
SELECT COUNT(last_name) FROM employees;
#3.是否忽略null
SELECT SUM(commission_pct),AVG(commission_pct) FROM employees;
SELECT commission_pct FROM employees;
SELECT SUM(commission_pct),AVG(commission_pct),SUM(commission_pct)/35,AVG(commission_pct)/107 FROM employees;
SELECT MAX(commission_pct),MIN(commission_pct) FROM employees;
SELECT COUNT(commission_pct) FROM employees;
#4.和distinct搭配
SELECT SUM(DISTINCT salary),SUM(salary) FROM employees;
SELECT COUNT(DISTINCT salary),COUNT(salary) FROM employees;
#5.count函数详解
SELECT COUNT(salary) FROM employees;
SELECT COUNT(*) FROM employees;
SELECT COUNT(1) FROM employees;
/*
效率上:
MyISAM存储引擎,count(*)最高
InnoDB存储引擎,count(*)和count(1)效率>count(字段)
*/
#6.和分组函数一同查询的字段有限制
SELECT AVG(salary),employee_id FROM employees;
6、分组查询
注意:查询列表必须特殊,要求是分组函数和group by后出现的字段
特点:
- 1.分组查询中的筛选条件分为两类
使用关键字 筛选的表 位置
分组前筛选 where 原始表 group by的前面
分组后筛选 having 分组后的结果 group by的后面
1.分组函数做条件肯定是放在having子句中
2.能用分组前筛选的,就优先考虑使用分组前筛选
- 2.group by子句支持单个字段分组,多个字段分组(多个字段之间用逗号隔开没有顺序要求),表达式或函数(使用较少)
- 3.也可以添加排序(排序放在整个分组查询的最后)
#引入:查询每个部门的平均工资
SELECT AVG(salary) FROM employees;
#案例1:查询每个工种的最高工资
SELECT MAX(salary),job_id FROM employees
GROUP BY job_id;
#案例2:查询每个位置上的部门个数
SELECT COUNT(*),location_id
FROM departments
GROUP BY location_id;
#添加筛选条件
#案例1:查询邮箱中包含a字符的,每个部门的平均工资
SELECT AVG(salary),department_id FROM employees
WHERE email LIKE '%a%' GROUP BY department_id;
#案例2:查询有奖金的每个领导手下员工的最高工资
SELECT MAX(salary),manager_id FROM employees
WHERE commission_pct IS NOT NULL
GROUP BY manager_id;
#添加复杂的筛选条件
#案例1:查询哪个部门的员工个数>2
#1.查询每个部门的员工个数
SELECT COUNT(*),department_id FROM employees
GROUP BY department_id;
#2.根据1的结果进行筛选,查询哪个部门的员工个数大于2
SELECT COUNT(*),department_id FROM employees
GROUP BY department_id HAVING COUNT(*)>2;
#案例2:查询每个工种有奖金的员工的最高工资>12000的工种编号和最高工资
#1.查询每个工种有奖金的员工的最高工资
SELECT MAX(salary),job_id FROM employees
WHERE commission_pct IS NOT NULL GROUP BY job_id;
#2.根据结果继续筛选,最高工资>12000
SELECT MAX(salary), job_id FROM employees
WHERE commission_pct IS NOT NULL GROUP BY job_id
HAVING MAX(salary)>12000;
#按表达式或函数分组
#案例:按员工姓名的长度分组,查询每一组的员工个数,筛选员工个数>5
#1.查询每个长度的员工个数
SELECT COUNT(*),LENGTH(last_name) len_name
FROM employees GROUP BY LENGTH(last_name);
#2.添加筛选条件
SELECT COUNT(*) c,LENGTH(last_name) len_name
FROM employees GROUP BY len_name HAVING c>5;
#按多个字段查询
#案例:查询每个部门每个工种的员工的平均工资
SELECT AVG(salary),department_id,job_id
FROM employees GROUP BY department_id,job_id;
#添加排序
#案例:查询每个部门每个工种的员工的平均工资,按平均工资的高低查询
SELECT AVG(salary),department_id,job_id
FROM employees GROUP BY department_id,job_id
ORDER BY AVG(salary) DESC;
连接查看另一篇博文
7、子查询
- 含义:出现在其他语句中的select语句,称为子查询或内查询外部的查询语句,称为主查询或外查询。
#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 Abel 高?
#①查询Abel的工资
SELECT salary
FROM employees
WHERE last_name = 'Abel';
#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 = 'Abel'
);
#案例2:返回job_id与141号员工相同,salary比143号员工多的员工 姓名,job_id 和工资
#①查询141号员工的job_id
SELECT job_id FROM employees
WHERE employee_id = 141;
#②查询143号员工的salary
SELECT salary FROM employees
WHERE employee_id = 143;
#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 = 141
) AND salary>(
SELECT salary
FROM employees
WHERE employee_id = 143
);
#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 = 250
);
#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: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 (
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
) 部门名;
#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 job_grades;
#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.`grade_level`
FROM (
SELECT AVG(salary) ag,department_id
FROM employees
GROUP BY department_id
) ag_dep
INNER JOIN job_grades g
ON ag_dep.ag BETWEEN lowest_sal AND highest_sal;
#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`
);
8、分页查询
· 应用场景:当要显示的数据,一页显示不全,需要分页提交sql请求。
①limit语句放在查询语句的最后
②公式
要显示的页数 page,每页的条目数size
select 查询列表 from 表
limit (page-1)*size,size;
size=10
page
1 0
2 10
3 20
案例
#案例1:查询前五条员工信息
SELECT * FROM employees LIMIT 0,5;
SELECT * FROM employees LIMIT 5;
#案例2:查询第11条——第25条
SELECT * FROM employees LIMIT 10,15;
#案例3:有奖金的员工信息,并且工资较高的前10名显示出来
SELECT * FROM employees
WHERE commission_pct IS NOT NULL
ORDER BY salary DESC LIMIT 10 ;
9、联合查询
含义:union (联合、合并):将多条查询语句的结果合并成一个结果。
· 语法
查询语句1
union【all】
查询语句2
union【all】
· 意义
· 1、将一条比较复杂的查询语句拆分成多条语句
· 2、适用于查询多个表的时候,查询的列基本是一致。
特点
· 1、要求多条查询语句的查询列数是一致的!
· 2、要求多条查询语句的查询的每一列的类型和顺序最好一致
· 3、union关键字默认去重,如果使用union all 可以包含重复项
案例
#引入的案例:查询部门编号>90或邮箱包含a的员工信息
SELECT * FROM employees WHERE email LIKE '%a%' OR department_id>90;
SELECT * FROM employees WHERE email LIKE '%a%'
UNION
SELECT * FROM employees WHERE department_id>90;
#案例:查询中国用户中男性的信息以及外国用户中年男性的用户信息
SELECT id,cname,csex FROM t_ca WHERE csex='男'
UNION
SELECT t_id,tName,tGender FROM t_ua WHERE tGender='male';
CREATE TABLE job_grades
(grade_level VARCHAR(3),
lowest_sal INT,
highest_sal INT);
INSERT INTO job_grades
VALUES ('A', 1000, 2999);
INSERT INTO job_grades
VALUES ('B', 3000, 5999);
INSERT INTO job_grades
VALUES('C', 6000, 9999);
INSERT INTO job_grades
VALUES('D', 10000, 14999);
INSERT INTO job_grades
VALUES('E', 15000, 24999);
INSERT INTO job_grades
VALUES('F', 25000, 40000);