1、准备数据源
/* SQLyog Ultimate v10.00 Beta1 MySQL - 5.5.15 : Database - myemployees ********************************************************************* */ /*!40101 SET NAMES utf8 */; /*!40101 SET SQL_MODE=''*/; /*!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.sum和avg一般用于处理数值型
#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);