Spring 与 JDBC模板：

　　为了避免直接使用 JDBC 而带来的复杂且冗长的代码，Spring 提供了一个强有力的模板类---JdbcTemplate 来简化 JDBC 操作。并且，数据源 DataSource 对象与模板 JdbcTemplate 对象均可通过 Bean 的形式定义在配置文件中，充分发挥了依赖注入的威力。

　　因此，对于 JDBC 模板的使用，是 IoC 的应用，是将数据源 DataSource 对象和 JDBC 模板对象注入给了 Dao 层的实现类。

　　代码详解：

　　　　（1）定义实体类 User

 package com.tongji.beans;

 public class Student {

     private Integer id;

     private String name;

     private int age;

     public Integer getId() {

         return id;

     }

     public void setId(Integer id) {

         this.id = id;

     }

     public String getName() {

         return name;

     }

     public void setName(String name) {

         this.name = name;

     }

     public int getAge() {

         return age;

     }

     public void setAge(int age) {

         this.age = age;

     }

     public Student() {

         super();

     }

     public Student(String name, int age) {

         super();

         this.name = name;

         this.age = age;

     }

     @Override

     public String toString() {

         return "Student [id=" + id + ", name=" + name + ", age=" + age + "]";

     }

 }

　　　　（2）定义数据库及表

　　　　（3）定义IStudentDao接口：

 package com.tongji.dao;

 import java.util.List;

 import com.tongji.beans.Student;

 public interface IStudentDao {

     void insertStudent(Student student);

     void deleteStudent(int id);

     void updateStudent(Student student);

     String selectStudentNameById(int id);

     List<String> selectStudentNames();

     Student selectStudentById(int id);

     List<Student> selectStudents();

 }

　　　　（4）定义IStudentDaoImpl实现类：

 package com.tongji.dao;

 import java.util.List;

 import org.springframework.jdbc.core.support.JdbcDaoSupport;

 import com.tongji.beans.Student;

 public class StudentDaoImpl extends JdbcDaoSupport implements IStudentDao {

     //JDBC模板对增删改的实现都是通过update方法

     @Override

     public void insertStudent(Student student) {

         String sql = "insert into student(name,age) value(?,?)";

         this.getJdbcTemplate().update(sql, student.getName(), student.getAge());

     }

     @Override

     public void deleteStudent(int id) {

         String sql = "delete from student where id = ?";

         this.getJdbcTemplate().update(sql, id);

     }

     @Override

     public void updateStudent(Student student) {

         String sql = "update student set name = ?, age = ? where id = ?";

         this.getJdbcTemplate().update(sql, student.getName(), student.getAge(), student.getId());

     }

     @Override

     public String selectStudentNameById(int id) {

         String sql = "select name from student where id = ?";

         return this.getJdbcTemplate().queryForObject(sql, String.class, id);

     }

     @Override

     public List<String> selectStudentNames() {

         String sql = "select name from student";

         return this.getJdbcTemplate().queryForList(sql, String.class);

     }

     @Override

     public Student selectStudentById(int id) {

         String sql = "select * from student where id = ?";

         return (Student) this.getJdbcTemplate().queryForObject(sql, new StudentRowMapper(), id);

     }

     @Override

     public List<Student> selectStudents() {

         String sql = "select * from student";

         return this.getJdbcTemplate().query(sql, new StudentRowMapper());

     }

 }

　　对Dao实现类的解释：

　　（1） 继承JdbcDaoSupport 类的作用：

　　　　Dao 实现类继承 JdbcDaoSupport 类，JdbcDaoSupport 类中有一个属性 JdbcTemplate，用于接收 JDBC 模板。所以 Dao 实现类继承了 JdbcDaoSupport 类后，也就具有了 JDBC 模板属性。在配置文件中，只要将模板对象注入即可。　　 
　　　　再仔细查看 JdbcDaoSupport 类，发现其有一个 dataSource 属性，查看 setDataSource()方法体可知，若 JDBC 模板为 null，则会自动创建一个模板对象。

　　　　所以，在 Spring 配置文件中，对于 JDBC 模板对象的配置完全可以省去，而是在 Dao 实现类中直接注入数据源对象。这样会让系统自动创建 JDBC 模板对象。

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" 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alt="" width="671" height="434" />

　　（2） JdbcTemplate 类对数据库的操作方法：

　　　　JdbcTemplate 类中提供了对 DB 进行修改、查询的方法。Dao 实现类使用继承自JdbcDaoSupport 的 getTemplate()方法，可以获取到 JDBC 模板对象。

　　　　（1）对 DB 的增、删、改都是通过 update()方法实现的。该方法常用的重载方法有两个：

　　　　　　public int update ( String sql)
　　　　　　public int update ( String sql, Object… args)  
　　　　第 1 个参数为要执行的 sql 语句，第 2 个参数为要执行的 sql 语句中所包含的动态参数。其返回值为所影响记录的条数。一般不用。

　　　　（2）JDBC 模板的查询结果均是以对象的形式返回。根据返回对象类型的不同，可以将查询分为两类：简单对象查询，与自定义对象查询。  
　　　　　　简单对象查询：查询结果为 String、Integer 等简单对象类型，或该类型做为元素的集合类型，如 List<String>等。  
　　　　　　自定义对象查询：查询结果为自定义类型，如 User 等，或该类型做为元素的集合类型，如 List<User>等。
　　　   　　（1）简单对象查询
　　　　　　　　常用的简单对象查询方法有：查询结果为单个对象的 queryForObject()与查询结果为 List的 queryForList()。  
　　　　　　　　　　pubic T queryForObject (String sql, Class<T> type, Object... args)
　　　　　　　　　　pubic List<T> queryForList (String sql, Class<T> type, Object... args)

　　　　　　（2）自定义对象查询
　　　　　　　　常用的自定义对象查询方法有：查询结果为单个对象的 queryForObject()与查询结果为List 的 query()。  
　　　　　　　　　　pubic T queryForObject (String sql, RowMapper<T> m , Object... args)
　　　　　　　　　　pubic List<T> query (String sql, RowMapper<T > m, Object... args)  
　　　　　　　　注意，RowMapper 为记录映射接口，用于将查询结果集中每一条记录包装为指定对象。该接口中有一个方法需要实现：
　　　　　　　　　　public Object mapRow(ResultSet rs, int rowNum)  
　　　　　　　　参数 rowNum 表示总的结果集中当前行的行号，但参数 rs 并不表示总的结果集，而是表示 rowNum 所代表的当前行的记录所定义的结果集，仅仅是当前行的结果。  
　　　　　　　　一般，该方法体中就是实现将查询结果中当前行的数据包装为一个指定对象。

　　　　　　　　自定义的RowMapper实现类：

package com.tongji.dao;

import java.sql.ResultSet;

import java.sql.SQLException;

import org.springframework.jdbc.core.RowMapper;

import com.tongji.beans.Student;

//将数据库中的一行记录包装为一个对象

public class StudentRowMapper implements RowMapper<Student> {

    //rs:查询总结果集中，当前遍历的这一行

    //rowNum:当前遍历的行号

    @Override

    public Student mapRow(ResultSet rs, int rowNum) throws SQLException {

        Student student = new Student();

        //从rs中读取数据，并将其包装为student对象

        student.setId(rs.getInt("id"));

        student.setName(rs.getString("name"));

        student.setAge(rs.getInt("age"));

        return student;

    }

}

　　　　（5）定义IStudentService接口：

 package com.tongji.service;

 import java.util.List;

 import com.tongji.beans.Student;

 public interface IStudentService {

     void addStudent(Student student);

     void removeStudent(int id);

     void modifyStudent(Student student);

     String findStudentNameById(int id);

     List<String> findStudentNames();

     Student findStudentById(int id);

     List<Student> findStudents();

 }

　　　　（6）定义IStudentServiceImpl实现类：

 package com.tongji.service;

 import java.util.List;

 import com.tongji.beans.Student;

 import com.tongji.dao.IStudentDao;

 public class StudentServiceImpl implements IStudentService {

     private IStudentDao dao;

     public void setDao(IStudentDao dao) {

         this.dao = dao;

     }

     @Override

     public void addStudent(Student student) {

         dao.insertStudent(student);

     }

     @Override

     public void removeStudent(int id) {

         dao.deleteStudent(id);

     }

     @Override

     public void modifyStudent(Student student) {

         dao.updateStudent(student);

     }

     @Override

     public String findStudentNameById(int id) {

         return dao.selectStudentNameById(id);

     }

     @Override

     public List<String> findStudentNames() {

         return dao.selectStudentNames();

     }

     @Override

     public Student findStudentById(int id) {

         return dao.selectStudentById(id);

     }

     @Override

     public List<Student> findStudents() {

         return dao.selectStudents();

     }

 }

　　　　（7）配置Spring配置文件：

 <?xml version="1.0" encoding="UTF-8"?>

 <beans xmlns="http://www.springframework.org/schema/beans"

     xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"

     xmlns:context="http://www.springframework.org/schema/context" xsi:schemaLocation="

         http://www.springframework.org/schema/beans

         http://www.springframework.org/schema/beans/spring-beans.xsd

         http://www.springframework.org/schema/context

         http://www.springframework.org/schema/context/spring-context.xsd">

     <!-- 注册数据源：Spring默认的数据源 -->

     <!-- <bean id="myDataSource" class="org.springframework.jdbc.datasource.DriverManagerDataSource">

         <property name="driverClassName" value="com.mysql.jdbc.Driver" />

         <property name="url" value="jdbc:mysql:///mytest" />

         <property name="username" value="root" />

         <property name="password" value="248xiaohai" />

     </bean> -->

     <!-- 注册数据源：DBCP数据源 -->

     <!--<bean id="myDataSource" class="org.apache.commons.dbcp.BasicDataSource">

         <property name="driverClassName" value="com.mysql.jdbc.Driver" />

         <property name="url" value="jdbc:mysql:///mytest" />

         <property name="username" value="root" />

         <property name="password" value="248xiaohai" />

     </bean> -->

     <!-- 注册数据源：C3P0数据源 -->

     <!-- <bean id="myDataSource" class="com.mchange.v2.c3p0.ComboPooledDataSource">

         <property name="driverClass" value="com.mysql.jdbc.Driver" />

         <property name="jdbcUrl" value="jdbc:mysql:///mytest" />

         <property name="user" value="root" />

         <property name="password" value="248xiaohai" />

     </bean> -->

     <bean id="myDataSource" class="com.mchange.v2.c3p0.ComboPooledDataSource">

         <property name="driverClass" value="${jdbc.driverClass}" />

         <property name="jdbcUrl" value="${jdbc.url}" />

         <property name="user" value="${jdbc.user}" />

         <property name="password" value="${jdbc.password}" />

     </bean>

     <!-- 注册JDBC属性文件 -->

     <!-- <bean class="org.springframework.beans.factory.config.PropertyPlaceholderConfigurer">

         <property name="location" value="classpath:jdbc.properties"/>

      </bean> -->

     <!-- 注册JDBC属性文件 -->

     <context:property-placeholder location="classpath:jdbc.properties"/>

     <!-- 注册JDBC模板对象,不用注册-->

     <!-- <bean id="myJdbcTemplate" class="org.springframework.jdbc.core.JdbcTemplate">

         <property name="dataSource" ref="myDataSource"/>

     </bean>

     <bean id="studentDao" class="com.tongji.dao.StudentDaoImpl">

         <property name="jdbcTemplate" ref="myJdbcTemplate"/>

     </bean> -->

     <!-- 注册Dao -->

     <bean id="studentDao" class="com.tongji.dao.StudentDaoImpl">

         <property name="dataSource" ref="myDataSource"/>

     </bean>

     <!-- 注册Service -->

     <bean id="studentService" class="com.tongji.service.StudentServiceImpl">

         <property name="dao" ref="studentDao"></property>

     </bean>

 </beans>

　　　　Spring配置文件的解释：

　　　　（1）数据源的配置
　　　　　　使用 JDBC 模板，首先需要配置好数据源，数据源直接以 Bean 的形式配置在 Spring 配置文件中。根据数据源的不同，其配置方式不同。下面主要讲解三种常用数据源的配置方式：  
　　　　　　　　（1）Spring 默认的数据源  
　　　　　　　　（2）DBCP 数据源  
　　　　　　　　（3）C3P0 数据源
　　　　（2）从属性文件读取数据库连接信息
　　　　　　为了便于维护，可以将数据库连接信息写入到属性文件中，使 Spring 配置文件从中读取数据。属性文件名称随意，但一般都是放在 src 下。

　　　　　　Spring 配置文件从属性文件中读取数据时，需要在<property/>的 value 属性中使用${ }，将在属性文件中定义的 key 括起来，以引用指定属性的值。

　　　　　　该属性文件若要被 Spring 配置文件读取，其必须在配置文件中进行注册。注册方式有两种：  
　　　　　　　　（1）<bean/>方式  
　　　　　　　　（2）<context>方式  （见代码）
　　　　（3）Dao和Service的配置：

　　　　　　注意：Dao只要手动注入数据源对象。

　　　　（8） 测试类：

 package com.tongji.test;

 import java.util.List;

 import org.junit.Before;

 import org.junit.Test;

 import org.springframework.context.ApplicationContext;

 import org.springframework.context.support.ClassPathXmlApplicationContext;

 import com.tongji.beans.Student;

 import com.tongji.service.IStudentService;

 public class MyTest {

     private IStudentService service;

     @Before

     public void before() {

         //创建容器

         @SuppressWarnings("resource")

         ApplicationContext ac = new ClassPathXmlApplicationContext("applicationContext.xml");

         service = (IStudentService) ac.getBean("studentService");

     }

     @Test

     public void testAdd() {

         service.addStudent(new Student("张三", 23));

     }

     @Test

     public void testRemove() {

         service.removeStudent(1);

     }

     @Test

     public void testModify() {

         Student student = new Student("李四", 24);

         student.setId(2);

         service.modifyStudent(student);

     }

     @Test

     public void testFindNameById() {

         String name = service.findStudentNameById(2);

         System.out.println(name);

     }

     @Test

     public void testFindStudentNames() {

         List<String> name = service.findStudentNames();

         System.out.println(name);

     }

     @Test

     public void testFindStudentById() {

         Student student = service.findStudentById(2);

         System.out.println(student);

     }

     @Test

     public void testFindStudents() {

         List<Student> students = service.findStudents();

         for (Student student : students) {

             System.out.println(student);

         }

     }

 }

　　补充：JDBC 模板对象是多例的
　　　　JdbcTemplate 对象是多例的，即系统会为每一个使用模板对象的线程（方法）创建一个JdbcTemplate 实例，并且在该线程（方法）结束时，自动释放 JdbcTemplate 实例。所以在每次使用 JdbcTemplate 对象时，都需要通过 getJdbcTemplate()方法获取。