DQL-数据查询语言

2020-12-27 20:32:34 阅读：158 来源： 互联网

标签：03 00 employees DQL 查询语言 NULL 数据 id SELECT

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');

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】
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;

标签：03,00,employees,DQL,查询语言,NULL,数据,id,SELECT
来源： https://www.cnblogs.com/HelloM/p/14198524.html

本站声明： 1. iCode9 技术分享网（下文简称本站）提供的所有内容，仅供技术学习、探讨和分享；
2. 关于本站的所有留言、评论、转载及引用，纯属内容发起人的个人观点，与本站观点和立场无关；
3. 关于本站的所有言论和文字，纯属内容发起人的个人观点，与本站观点和立场无关；
4. 本站文章均是网友提供，不完全保证技术分享内容的完整性、准确性、时效性、风险性和版权归属；如您发现该文章侵犯了您的权益，可联系我们第一时间进行删除；
5. 本站为非盈利性的个人网站，所有内容不会用来进行牟利，也不会利用任何形式的广告来间接获益，纯粹是为了广大技术爱好者提供技术内容和技术思想的分享性交流网站。

ICode9