在实际开发过程中，同一个项目很可能需要多个数据源进行支持，所以今天我把自己整合Mybatis多数据源的过程和大家分享下。

添加所需依赖

<!--mysql连接驱动 --> <dependency> <groupId>mysql</groupId> <artifactId>mysql-connector-java</artifactId> <scope>runtime</scope> </dependency> <!--通用mapper --> <dependency> <groupId>tk.mybatis</groupId> <artifactId>mapper-spring-boot-starter</artifactId> <version>1.1.0</version> </dependency>  <!--druid数据源 --> <dependency> <groupId>com.alibaba</groupId> <artifactId>druid</artifactId> <version>1.0.25</version> </dependency>123456789101112131415161718192021

这里为了测试方便引用了Mybatis通用mapper插件，只适合对单表的增删改进行操作，避免了xml的配置和手写sql，特别方便。大家也可以利用常规方式进行测试，这里不做过多解释。在application.properties配置文件进行相关配置。我们配置了两个数据源，一个作为主数据源，另一个作为从数据源。

# master 主数据源配置master.datasource.url=jdbc:mysql://localhost/master?useUnicode=true&characterEncoding=utf8master.datasource.username=rootmaster.datasource.password=rootmaster.datasource.driverClassName=com.mysql.jdbc.Driver# cluster 从数据源配置cluster.datasource.url=jdbc:mysql://localhost/cluster?useUnicode=true&characterEncoding=utf8cluster.datasource.username=rootcluster.datasource.password=rootcluster.datasource.driverClassName=com.mysql.jdbc.Driver#连接池的配置信息## 初始化大小，最小，最大spring.druid.initialSize=5spring.druid.minIdle=5spring.druid.maxActive=20## 配置获取连接等待超时的时间spring.druid.maxWait=60000# 配置间隔多久才进行一次检测，检测需要关闭的空闲连接，单位是毫秒spring.druid.timeBetweenEvictionRunsMillis=60000# 配置一个连接在池中最小生存的时间，单位是毫秒spring.druid.minEvictableIdleTimeMillis=300000spring.druid.validationQuery=SELECT 1 FROM DUALspring.druid.testWhileIdle=truespring.druid.testOnBorrow=falsespring.druid.testOnReturn=falsespring.druid.poolPreparedStatements=truespring.druid.maxPoolPreparedStatementPerConnectionSize=20# 配置监控统计拦截的filters，去掉后监控界面sql无法统计，'wall'用于防火墙spring.druid.filters=stat,wall,log4j# 通过connectProperties属性来打开mergeSql功能；慢SQL记录spring.druid.connectionProperties=druid.stat.mergeSql=true;druid.stat.slowSqlMillis=500012345678910111213141516171819202122232425262728293031323334

@Configuration// 扫描 Mapper@MapperScan(basePackages = MasterDataSourceConfig.MASTER_PACKAGE, sqlSessionFactoryRef = "masterSqlSessionFactory")public class MasterDataSourceConfig { //扫描从数据源mapper接口所在的包 static final String MASTER_PACKAGE = "cn.jj.mapper.master"; //扫描从数据源xml文件 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(); }}123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051

@Configuration//扫描 Mapper @MapperScan(basePackages = ClusterDataSourceConfig.CLASTER_PACKAGE, sqlSessionFactoryRef = "clusterSqlSessionFactory")public class ClusterDataSourceConfig { //扫描从数据源mapper接口所在的包 static final String CLASTER_PACKAGE = "cn.jj.mapper.cluster"; //扫描从数据源xml文件 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(); }}123456789101112131415161718192021222324252627282930313233343536373839404142434445464748

到这里Mybatis多数据源已经配置好，需要注意的是，主，从数据源一定要配置正确，特别是以下位置一定要和工程目录对应正确。

数据库数据信息

主数据库：

从数据库：

编写测试类测试

@RunWith(SpringRunner.class)@SpringBootTestpublic class MapperTest2 { @Autowired private CityService cityService; @Autowired private UserService userService; // 查询主表 @Test public void selectCity() { List<City> city = cityService.selectAll(); System.out.println("主表信息如下:"); for (City city2 : city) { System.out.println( "id:"+ city2.getId() + "\t" + "name:" + city2.getName() + "\t" + "state:" + city2.getState()); } } // 查询从表 @Test public void selectUser() { try { List<User> user = userService.searchAll(); System.out.println("从表信息如下:"); for (User user2 : user) { System.out.println("id:"+user2.getId() + "\t" + user2.getGender() + "\t" + user2.getName()); } } catch (Exception e) { e.printStackTrace(); } }}1234567891011121314151617181920212223242526272829303132333435363738

控制台输出信息如下：

spring boot 整合Mabatis 配置多数据源完成。