我们在开发一个项目的时候,可能会遇到需要对多个数据库进行读写的需求,这时候就得在项目中配置多个数据源了。在Java项目的开发中,目前最常用的数据操作框架是 Mybatis,开发框架也都基本用上了SpringBoot。而Druid号称最好的数据库连接池,自然也是被广泛使用。
所以本文将演示一下,SpringBoot+Druid+Mybatis如何去配置多数据源。首先在IDEA中创建一个SpringBoot工程:
选择一些基本的包:
完成创建:
pom.xml配置的依赖如下:
<dependencies>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-web</artifactId>
</dependency>
<dependency>
<groupId>org.mybatis.spring.boot</groupId>
<artifactId>mybatis-spring-boot-starter</artifactId>
<version>1.3.2</version>
</dependency>
<dependency>
<groupId>mysql</groupId>
<artifactId>mysql-connector-java</artifactId>
<scope>runtime</scope>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-test</artifactId>
<scope>test</scope>
</dependency>
<!-- alibaba的druid数据库连接池 -->
<dependency>
<groupId>com.alibaba</groupId>
<artifactId>druid-spring-boot-starter</artifactId>
<version>1.1.9</version>
</dependency>
</dependencies>
接着就是编辑SpringBoot的配置文件,我这里使用的是yml格式的。需要注意的是,在使用多数据源的情况下,必须区分出主数据源和从数据源,否则会报错。application.yml配置文件内容如下:
spring:
datasource:
#使用druid连接池
type: com.alibaba.druid.pool.DruidDataSource
# 自定义的主数据源配置信息
primary:
datasource:
#druid相关配置
druid:
#监控统计拦截的filters
filters: stat
driverClassName: com.mysql.jdbc.Driver
#配置基本属性
url: jdbc:mysql://127.0.0.1:3306/primary_database?useUnicode=true&characterEncoding=UTF-8&allowMultiQueries=true&autoReconnect=true&useSSL=false
username: root
password: password
#配置初始化大小/最小/最大
initialSize: 1
minIdle: 1
maxActive: 20
#获取连接等待超时时间
maxWait: 60000
#间隔多久进行一次检测,检测需要关闭的空闲连接
timeBetweenEvictionRunsMillis: 60000
#一个连接在池中最小生存的时间
minEvictableIdleTimeMillis: 300000
validationQuery: SELECT ‘x‘
testWhileIdle: true
testOnBorrow: false
testOnReturn: false
#打开PSCache,并指定每个连接上PSCache的大小。oracle设为true,mysql设为false。分库分表较多推荐设置为false
poolPreparedStatements: false
maxPoolPreparedStatementPerConnectionSize: 20
# 自定义的从数据源配置信息
back:
datasource:
#druid相关配置
druid:
#监控统计拦截的filters
filters: stat
driverClassName: com.mysql.jdbc.Driver
#配置基本属性
url: jdbc:mysql://127.0.0.1:3306/back_database?useUnicode=true&characterEncoding=UTF-8&allowMultiQueries=true&autoReconnect=true&useSSL=false
username: root
password: password
#配置初始化大小/最小/最大
initialSize: 1
minIdle: 1
maxActive: 20
#获取连接等待超时时间
maxWait: 60000
#间隔多久进行一次检测,检测需要关闭的空闲连接
timeBetweenEvictionRunsMillis: 60000
#一个连接在池中最小生存的时间
minEvictableIdleTimeMillis: 300000
validationQuery: SELECT ‘x‘
testWhileIdle: true
testOnBorrow: false
testOnReturn: false
#打开PSCache,并指定每个连接上PSCache的大小。oracle设为true,mysql设为false。分库分表较多推荐设置为false
poolPreparedStatements: false
maxPoolPreparedStatementPerConnectionSize: 20
然后在项目中新建一个config包,并在该包下创建一个PrimaryDataBaseConfig类,作为我们的主数据源配置类,用于加载自定义的主数据源配置信息,以及创建数据源和会话连接工厂等实例:
package com.dabo.mini.game.zhaxinle.config;
import com.alibaba.druid.pool.DruidDataSource;
import lombok.Data;
import org.apache.ibatis.session.SqlSessionFactory;
import org.mybatis.spring.SqlSessionFactoryBean;
import org.mybatis.spring.annotation.MapperScan;
import org.springframework.beans.factory.annotation.Qualifier;
import org.springframework.boot.context.properties.ConfigurationProperties;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.context.annotation.Primary;
import org.springframework.core.io.support.PathMatchingResourcePatternResolver;
import org.springframework.jdbc.datasource.DataSourceTransactionManager;
import javax.sql.DataSource;
import java.sql.SQLException;
/**
* @ProjectName zhaxinle
* @Author: zeroJun
* @Date: 2018/8/16 16:49
* @Description: 主数据源配置类
*/
@Data
@Configuration
// 前缀为primary.datasource.druid的配置信息
@ConfigurationProperties(prefix = "primary.datasource.druid")
@MapperScan(basePackages = PrimaryDataBaseConfig.PACKAGE, sqlSessionFactoryRef = "primarySqlSessionFactory")
public class PrimaryDataBaseConfig {
/**
* dao层的包路径
*/
static final String PACKAGE = "com.dabo.mini.game.zhaxinle.dao.primary";
/**
* mapper文件的相对路径
*/
private static final String MAPPER_LOCATION = "classpath:mappers/primary/*.xml";
private String filters;
private String url;
private String username;
private String password;
private String driverClassName;
private int initialSize;
private int minIdle;
private int maxActive;
private long maxWait;
private long timeBetweenEvictionRunsMillis;
private long minEvictableIdleTimeMillis;
private String validationQuery;
private boolean testWhileIdle;
private boolean testOnBorrow;
private boolean testOnReturn;
private boolean poolPreparedStatements;
private int maxPoolPreparedStatementPerConnectionSize;
// 主数据源使用@Primary注解进行标识
@Primary
@Bean(name = "primaryDataSource")
public DataSource primaryDataSource() throws SQLException {
DruidDataSource druid = new DruidDataSource();
// 监控统计拦截的filters
druid.setFilters(filters);
// 配置基本属性
druid.setDriverClassName(driverClassName);
druid.setUsername(username);
druid.setPassword(password);
druid.setUrl(url);
//初始化时建立物理连接的个数
druid.setInitialSize(initialSize);
//最大连接池数量
druid.setMaxActive(maxActive);
//最小连接池数量
druid.setMinIdle(minIdle);
//获取连接时最大等待时间,单位毫秒。
druid.setMaxWait(maxWait);
//间隔多久进行一次检测,检测需要关闭的空闲连接
druid.setTimeBetweenEvictionRunsMillis(timeBetweenEvictionRunsMillis);
//一个连接在池中最小生存的时间
druid.setMinEvictableIdleTimeMillis(minEvictableIdleTimeMillis);
//用来检测连接是否有效的sql
druid.setValidationQuery(validationQuery);
//建议配置为true,不影响性能,并且保证安全性。
druid.setTestWhileIdle(testWhileIdle);
//申请连接时执行validationQuery检测连接是否有效
druid.setTestOnBorrow(testOnBorrow);
druid.setTestOnReturn(testOnReturn);
//是否缓存preparedStatement,也就是PSCache,oracle设为true,mysql设为false。分库分表较多推荐设置为false
druid.setPoolPreparedStatements(poolPreparedStatements);
// 打开PSCache时,指定每个连接上PSCache的大小
druid.setMaxPoolPreparedStatementPerConnectionSize(maxPoolPreparedStatementPerConnectionSize);
return druid;
}
// 创建该数据源的事务管理
@Primary
@Bean(name = "primaryTransactionManager")
public DataSourceTransactionManager primaryTransactionManager() throws SQLException {
return new DataSourceTransactionManager(primaryDataSource());
}
// 创建Mybatis的连接会话工厂实例
@Primary
@Bean(name = "primarySqlSessionFactory")
public SqlSessionFactory primarySqlSessionFactory(@Qualifier("primaryDataSource") DataSource primaryDataSource) throws Exception {
final SqlSessionFactoryBean sessionFactory = new SqlSessionFactoryBean();
sessionFactory.setDataSource(primaryDataSource); // 设置数据源bean
sessionFactory.setMapperLocations(new PathMatchingResourcePatternResolver()
.getResources(PrimaryDataBaseConfig.MAPPER_LOCATION)); // 设置mapper文件路径
return sessionFactory.getObject();
}
}
同样的,还需要创建一个从数据源配置类,与主数据源配置类不同的是,从数据源配置类不能使用@Primary
注解,即表示它是一个从数据源。代码如下:
package com.dabo.mini.game.zhaxinle.config;
import com.alibaba.druid.pool.DruidDataSource;
import lombok.Data;
import org.apache.ibatis.session.SqlSessionFactory;
import org.mybatis.spring.SqlSessionFactoryBean;
import org.mybatis.spring.annotation.MapperScan;
import org.springframework.beans.factory.annotation.Qualifier;
import org.springframework.boot.context.properties.ConfigurationProperties;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.core.io.support.PathMatchingResourcePatternResolver;
import org.springframework.jdbc.datasource.DataSourceTransactionManager;
import javax.sql.DataSource;
import java.sql.SQLException;
/**
* @ProjectName zhaxinle
* @Author: zeroJun
* @Date: 2018/8/16 16:49
* @Description: 后台数据源配置类
*/
@Data
@Configuration
@ConfigurationProperties(prefix = "back.datasource.druid")
@MapperScan(basePackages = BackDataBaseConfig.PACKAGE, sqlSessionFactoryRef = "backSqlSessionFactory")
public class BackDataBaseConfig {
/**
* dao层的包路径
*/
static final String PACKAGE = "com.dabo.mini.game.zhaxinle.dao.back";
/**
* mapper文件的相对路径
*/
private static final String MAPPER_LOCATION = "classpath:mappers/back/*.xml";
private String filters;
private String url;
private String username;
private String password;
private String driverClassName;
private int initialSize;
private int minIdle;
private int maxActive;
private long maxWait;
private long timeBetweenEvictionRunsMillis;
private long minEvictableIdleTimeMillis;
private String validationQuery;
private boolean testWhileIdle;
private boolean testOnBorrow;
private boolean testOnReturn;
private boolean poolPreparedStatements;
private int maxPoolPreparedStatementPerConnectionSize;
@Bean(name = "backDataSource")
public DataSource backDataSource() throws SQLException {
DruidDataSource druid = new DruidDataSource();
// 监控统计拦截的filters
druid.setFilters(filters);
// 配置基本属性
druid.setDriverClassName(driverClassName);
druid.setUsername(username);
druid.setPassword(password);
druid.setUrl(url);
//初始化时建立物理连接的个数
druid.setInitialSize(initialSize);
//最大连接池数量
druid.setMaxActive(maxActive);
//最小连接池数量
druid.setMinIdle(minIdle);
//获取连接时最大等待时间,单位毫秒。
druid.setMaxWait(maxWait);
//间隔多久进行一次检测,检测需要关闭的空闲连接
druid.setTimeBetweenEvictionRunsMillis(timeBetweenEvictionRunsMillis);
//一个连接在池中最小生存的时间
druid.setMinEvictableIdleTimeMillis(minEvictableIdleTimeMillis);
//用来检测连接是否有效的sql
druid.setValidationQuery(validationQuery);
//建议配置为true,不影响性能,并且保证安全性。
druid.setTestWhileIdle(testWhileIdle);
//申请连接时执行validationQuery检测连接是否有效
druid.setTestOnBorrow(testOnBorrow);
druid.setTestOnReturn(testOnReturn);
//是否缓存preparedStatement,也就是PSCache,oracle设为true,mysql设为false。分库分表较多推荐设置为false
druid.setPoolPreparedStatements(poolPreparedStatements);
// 打开PSCache时,指定每个连接上PSCache的大小
druid.setMaxPoolPreparedStatementPerConnectionSize(maxPoolPreparedStatementPerConnectionSize);
return druid;
}
@Bean(name = "backTransactionManager")
public DataSourceTransactionManager backTransactionManager() throws SQLException {
return new DataSourceTransactionManager(backDataSource());
}
@Bean(name = "backSqlSessionFactory")
public SqlSessionFactory backSqlSessionFactory(@Qualifier("backDataSource") DataSource backDataSource) throws Exception {
final SqlSessionFactoryBean sessionFactory = new SqlSessionFactoryBean();
sessionFactory.setDataSource(backDataSource);
sessionFactory.setMapperLocations(new PathMatchingResourcePatternResolver()
.getResources(BackDataBaseConfig.MAPPER_LOCATION));
return sessionFactory.getObject();
}
}
完成以上配置后,该工程就具有连接两个数据库的能力了,如果要配置两个以上的数据库也是一样的,配置多个从数据源即可。业务代码层面除了需要将不同的数据源相关的mapper、dao、pojo分包存放方便扫描之外,代码上的编写还是和之前单数据源的时候一样,所以这里就不贴出业务代码了。
原文地址:http://blog.51cto.com/zero01/2161509
时间: 2024-10-03 16:47:27