目前业界操作数据库的框架一般是 Mybatis，但在很多业务场景下，我们需要在一个工程里配置多个数据源来实现业务逻辑。在SpringBoot中也可以实现多数据源并配合Mybatis框架编写xml文件来执行SQL。在SpringBoot中，配置多数据源的方式十分便捷，
下面开始上代码：
在pom.xml文件中需要添加一些依赖
<!-- Spring Boot Mybatis 依赖 --> <dependency> <groupId>org.mybatis.spring.boot</groupId> <artifactId>mybatis-spring-boot-starter</artifactId> <version>1.2.0</version> </dependency> <!-- MySQL 连接驱动依赖 --> <dependency> <groupId>mysql</groupId> <artifactId>mysql-connector-java</artifactId> <version>5.1.39</version> </dependency> <!-- Druid 数据连接池依赖 --> <dependency> <groupId>com.alibaba</groupId> <artifactId>druid</artifactId> <version>1.0.18</version> </dependency>
application.properties 配置两个数据源配置
# master 数据源配置 master.datasource.url=jdbc:mysql://localhost:3306/springbootdb?useUnicode=true&characterEncoding=utf8 master.datasource.username=root master.datasource.password=xieshuai6666 master.datasource.driverClassName=com.mysql.jdbc.Driver # second 数据源配置 second.datasource.url=jdbc:mysql://localhost:3306/springbootdb_second?useUnicode=true&characterEncoding=utf8 second.datasource.username=root second.datasource.password=xieshuai6666 second.datasource.driverClassName=com.mysql.jdbc.Driver
数据源配置
多数据源配置的时候注意，必须要有一个主数据源，即 MasterDataSourceConfig 配置
MasterDataSourceConfig的代码：
@Configuration
// 扫描 Mapper 接口并容器管理
@MapperScan(basePackages = MasterDataSourceConfig.PACKAGE, sqlSessionFactoryRef = "masterSqlSessionFactory")
public class MasterDataSourceConfig {
// 精确到 master 目录，以便跟其他数据源隔离
static final String PACKAGE = "org.spring.springboot.dao.master";
static final String MAPPER_LOCATION = "classpath:mapper/master/*.xml";
@Value("${master.datasource.url}")
private String url;
@Value("${master.datasource.username}")
private String user;
@Value("${master.datasource.password}")
private String password;
@Value("${master.datasource.driverClassName}")
private String driverClass;
@Bean(name = "masterDataSource")
@Primary
public DataSource masterDataSource() {
DruidDataSource dataSource = new DruidDataSource();
dataSource.setDriverClassName(driverClass);
dataSource.setUrl(url);
dataSource.setUsername(user);
dataSource.setPassword(password);
return dataSource;
}
@Bean(name = "masterTransactionManager")
@Primary
public DataSourceTransactionManager masterTransactionManager() {
return new DataSourceTransactionManager(masterDataSource());
}
@Bean(name = "masterSqlSessionFactory")
@Primary
public SqlSessionFactory masterSqlSessionFactory(@Qualifier("masterDataSource") DataSource masterDataSource)
throws Exception {
final SqlSessionFactoryBean sessionFactory = new SqlSessionFactoryBean();
sessionFactory.setDataSource(masterDataSource);
sessionFactory.setMapperLocations(new PathMatchingResourcePatternResolver()
.getResources(MasterDataSourceConfig.MAPPER_LOCATION));
return sessionFactory.getObject();
}
}
第二个数据源SecondDataSourceConfig的配置如下:
@Configuration
// 扫描 Mapper 接口并容器管理
@MapperScan(basePackages = ClusterDataSourceConfig.PACKAGE, sqlSessionFactoryRef = "clusterSqlSessionFactory")
public class ClusterDataSourceConfig {
// 精确到 cluster 目录，以便跟其他数据源隔离
static final String PACKAGE = "org.spring.springboot.dao.cluster";
static final String MAPPER_LOCATION = "classpath:mapper/cluster/*.xml";
@Value("${cluster.datasource.url}")
private String url;
@Value("${cluster.datasource.username}")
private String user;
@Value("${cluster.datasource.password}")
private String password;
@Value("${cluster.datasource.driverClassName}")
private String driverClass;
@Bean(name = "clusterDataSource")
public DataSource clusterDataSource() {
DruidDataSource dataSource = new DruidDataSource();
dataSource.setDriverClassName(driverClass);
dataSource.setUrl(url);
dataSource.setUsername(user);
dataSource.setPassword(password);
return dataSource;
}
@Bean(name = "clusterTransactionManager")
public DataSourceTransactionManager clusterTransactionManager() {
return new DataSourceTransactionManager(clusterDataSource());
}
@Bean(name = "clusterSqlSessionFactory")
public SqlSessionFactory clusterSqlSessionFactory(@Qualifier("clusterDataSource") DataSource clusterDataSource)
throws Exception {
final SqlSessionFactoryBean sessionFactory = new SqlSessionFactoryBean();
sessionFactory.setDataSource(clusterDataSource);
sessionFactory.setMapperLocations(new PathMatchingResourcePatternResolver()
.getResources(ClusterDataSourceConfig.MAPPER_LOCATION));
return sessionFactory.getObject();
}
}
到此，不同的数据源配置就已经完成，剩下的只需要将将Mybatis的xml文件和DAO层的接口写好，并在Service层注入，直接使用就行。
Service层的代码：
@Service
public class UserAndCityServiceImpl implements UserAndCityService{
@Autowired
private UserDao userDao;
@Autowired
private CityDao cityDao;
@Override
public UserVo getUser(String userName) {
UserVo userVo = userDao.selectByUserName(userName);
CityVo cityVo = cityDao.selectByCityName("北京市");
userVo.setDescription(cityVo.getCityName());
return userVo;
}
}
Mybatis的xml文件UserDao.xml和CityDao.xml的内容，就不一一展示了。
以上就是本文的全部内容，希望对大家的学习有所帮助，也希望大家多多支持脚本之家。
