在实际开发中, 有时候需要操作多个数据库, 使用切换数据源来实现此功能,也就是多数据源的配置
1. application-druid.yml (配置从库数据源)
# 数据源配置
spring:
datasource:
type: com.alibaba.druid.pool.DruidDataSource
driverClassName: com.mysql.cj.jdbc.Driver
druid:
# 主库数据源
master:
url: jdbc:mysql://8.134.xxx.xxx:3306/zc_travel?useUnicode=true&characterEncoding=utf8&zeroDateTimeBehavior=convertToNull&useSSL=true&serverTimezone=GMT%2B8
username: root
password: xxx
# 从库数据源
slave:
# 从数据源开关/默认关闭
enabled: true
url: jdbc:mysql://8.134.xxx.xxx:3306/test?useUnicode=true&characterEncoding=utf8&zeroDateTimeBehavior=convertToNull&useSSL=true&serverTimezone=GMT%2B8
username: root
password: xxx
# 初始连接数
initialSize: 5
# 最小连接池数量
minIdle: 10
# 最大连接池数量
maxActive: 20
# 配置获取连接等待超时的时间
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
timeBetweenEvictionRunsMillis: 60000
# 配置一个连接在池中最小生存的时间,单位是毫秒
minEvictableIdleTimeMillis: 300000
# 配置一个连接在池中最大生存的时间,单位是毫秒
maxEvictableIdleTimeMillis: 900000
# 配置检测连接是否有效
validationQuery: SELECT 1 FROM DUAL
testWhileIdle: true
testOnBorrow: false
testOnReturn: false
webStatFilter:
enabled: true
statViewServlet:
enabled: true
# 设置白名单,不填则允许所有访问
allow:
url-pattern: /druid/*
# 控制台管理用户名和密码
login-username: ruoyi
login-password: 123456
filter:
stat:
enabled: true
# 慢SQL记录
log-slow-sql: true
slow-sql-millis: 1000
merge-sql: true
wall:
config:
multi-statement-allow: true
2. DataSourceType.java (数据源枚举类)
/**
* 数据源
*
*/
public enum DataSourceType
{
/**
* 主库
*/
MASTER,
/**
* 从库
*/
SLAVE
}
3. DataSource.java (自定义多数据源切换注解)
import java.lang.annotation.Documented;
import java.lang.annotation.ElementType;
import java.lang.annotation.Inherited;
import java.lang.annotation.Retention;
import java.lang.annotation.RetentionPolicy;
import java.lang.annotation.Target;
import com.ruoyi.common.enums.DataSourceType;
/**
* 自定义多数据源切换注解
*
* 优先级:先方法,后类,如果方法覆盖了类上的数据源类型,以方法的为准,否则以类上的为准
*
*/
@Target({ ElementType.METHOD, ElementType.TYPE })
@Retention(RetentionPolicy.RUNTIME)
@Documented
@Inherited
public @interface DataSource
{
/**
* 切换数据源名称
*/
public DataSourceType value() default DataSourceType.MASTER;
}
4. DruidProperties.java (druid 配置属性)
import org.springframework.beans.factory.annotation.Value;
import org.springframework.context.annotation.Configuration;
import com.alibaba.druid.pool.DruidDataSource;
/**
* druid 配置属性
*
*/
@Configuration
public class DruidProperties
{
@Value("${spring.datasource.druid.initialSize}")
private int initialSize;
@Value("${spring.datasource.druid.minIdle}")
private int minIdle;
@Value("${spring.datasource.druid.maxActive}")
private int maxActive;
@Value("${spring.datasource.druid.maxWait}")
private int maxWait;
@Value("${spring.datasource.druid.timeBetweenEvictionRunsMillis}")
private int timeBetweenEvictionRunsMillis;
@Value("${spring.datasource.druid.minEvictableIdleTimeMillis}")
private int minEvictableIdleTimeMillis;
@Value("${spring.datasource.druid.maxEvictableIdleTimeMillis}")
private int maxEvictableIdleTimeMillis;
@Value("${spring.datasource.druid.validationQuery}")
private String validationQuery;
@Value("${spring.datasource.druid.testWhileIdle}")
private boolean testWhileIdle;
@Value("${spring.datasource.druid.testOnBorrow}")
private boolean testOnBorrow;
@Value("${spring.datasource.druid.testOnReturn}")
private boolean testOnReturn;
public DruidDataSource dataSource(DruidDataSource datasource)
{
/** 配置初始化大小、最小、最大 */
datasource.setInitialSize(initialSize);
datasource.setMaxActive(maxActive);
datasource.setMinIdle(minIdle);
/** 配置获取连接等待超时的时间 */
datasource.setMaxWait(maxWait);
/** 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 */
datasource.setTimeBetweenEvictionRunsMillis(timeBetweenEvictionRunsMillis);
/** 配置一个连接在池中最小、最大生存的时间,单位是毫秒 */
datasource.setMinEvictableIdleTimeMillis(minEvictableIdleTimeMillis);
datasource.setMaxEvictableIdleTimeMillis(maxEvictableIdleTimeMillis);
/**
* 用来检测连接是否有效的sql,要求是一个查询语句,常用select 'x'。如果validationQuery为null,testOnBorrow、testOnReturn、testWhileIdle都不会起作用。
*/
datasource.setValidationQuery(validationQuery);
/** 建议配置为true,不影响性能,并且保证安全性。申请连接的时候检测,如果空闲时间大于timeBetweenEvictionRunsMillis,执行validationQuery检测连接是否有效。 */
datasource.setTestWhileIdle(testWhileIdle);
/** 申请连接时执行validationQuery检测连接是否有效,做了这个配置会降低性能。 */
datasource.setTestOnBorrow(testOnBorrow);
/** 归还连接时执行validationQuery检测连接是否有效,做了这个配置会降低性能。 */
datasource.setTestOnReturn(testOnReturn);
return datasource;
}
}
5. DruidConfig.java (druid 配置多数据源)
import java.io.IOException;
import java.util.HashMap;
import java.util.Map;
import javax.servlet.Filter;
import javax.servlet.FilterChain;
import javax.servlet.ServletException;
import javax.servlet.ServletRequest;
import javax.servlet.ServletResponse;
import javax.sql.DataSource;
import org.springframework.boot.autoconfigure.condition.ConditionalOnProperty;
import org.springframework.boot.context.properties.ConfigurationProperties;
import org.springframework.boot.web.servlet.FilterRegistrationBean;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.context.annotation.Primary;
import com.alibaba.druid.pool.DruidDataSource;
import com.alibaba.druid.spring.boot.autoconfigure.DruidDataSourceBuilder;
import com.alibaba.druid.spring.boot.autoconfigure.properties.DruidStatProperties;
import com.alibaba.druid.util.Utils;
import com.ruoyi.common.enums.DataSourceType;
import com.ruoyi.common.utils.spring.SpringUtils;
import com.ruoyi.framework.config.properties.DruidProperties;
import com.ruoyi.framework.datasource.DynamicDataSource;
/**
* druid 配置多数据源
*/
@Configuration
public class DruidConfig
{
@Bean
@ConfigurationProperties("spring.datasource.druid.master")
public DataSource masterDataSource(DruidProperties druidProperties)
{
DruidDataSource dataSource = DruidDataSourceBuilder.create().build();
return druidProperties.dataSource(dataSource);
}
@Bean
@ConfigurationProperties("spring.datasource.druid.slave")
@ConditionalOnProperty(prefix = "spring.datasource.druid.slave", name = "enabled", havingValue = "true")
public DataSource slaveDataSource(DruidProperties druidProperties)
{
DruidDataSource dataSource = DruidDataSourceBuilder.create().build();
return druidProperties.dataSource(dataSource);
}
@Bean(name = "dynamicDataSource")
@Primary
public DynamicDataSource dataSource(DataSource masterDataSource)
{
Map<Object, Object> targetDataSources = new HashMap<>();
targetDataSources.put(DataSourceType.MASTER.name(), masterDataSource);
setDataSource(targetDataSources, DataSourceType.SLAVE.name(), "slaveDataSource");
return new DynamicDataSource(masterDataSource, targetDataSources);
}
/**
* 设置数据源
*
* @param targetDataSources 备选数据源集合
* @param sourceName 数据源名称
* @param beanName bean名称
*/
public void setDataSource(Map<Object, Object> targetDataSources, String sourceName, String beanName)
{
try
{
DataSource dataSource = SpringUtils.getBean(beanName);
targetDataSources.put(sourceName, dataSource);
}
catch (Exception e)
{
}
}
/**
* 去除监控页面底部的广告
*/
@SuppressWarnings({ "rawtypes", "unchecked" })
@Bean
@ConditionalOnProperty(name = "spring.datasource.druid.statViewServlet.enabled", havingValue = "true")
public FilterRegistrationBean removeDruidFilterRegistrationBean(DruidStatProperties properties)
{
// 获取web监控页面的参数
DruidStatProperties.StatViewServlet config = properties.getStatViewServlet();
// 提取common.js的配置路径
String pattern = config.getUrlPattern() != null ? config.getUrlPattern() : "/druid/*";
String commonJsPattern = pattern.replaceAll("\\*", "js/common.js");
final String filePath = "support/http/resources/js/common.js";
// 创建filter进行过滤
Filter filter = new Filter()
{
@Override
public void init(javax.servlet.FilterConfig filterConfig) throws ServletException
{
}
@Override
public void doFilter(ServletRequest request, ServletResponse response, FilterChain chain)
throws IOException, ServletException
{
chain.doFilter(request, response);
// 重置缓冲区,响应头不会被重置
response.resetBuffer();
// 获取common.js
String text = Utils.readFromResource(filePath);
// 正则替换banner, 除去底部的广告信息
text = text.replaceAll("<a.*?banner\"></a><br/>", "");
text = text.replaceAll("powered.*?shrek.wang</a>", "");
response.getWriter().write(text);
}
@Override
public void destroy()
{
}
};
FilterRegistrationBean registrationBean = new FilterRegistrationBean();
registrationBean.setFilter(filter);
registrationBean.addUrlPatterns(commonJsPattern);
return registrationBean;
}
}
6. DataSourceAspect.java (多数据源处理)
import java.util.Objects;
import org.aspectj.lang.ProceedingJoinPoint;
import org.aspectj.lang.annotation.Around;
import org.aspectj.lang.annotation.Aspect;
import org.aspectj.lang.annotation.Pointcut;
import org.aspectj.lang.reflect.MethodSignature;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.core.annotation.AnnotationUtils;
import org.springframework.core.annotation.Order;
import org.springframework.stereotype.Component;
import com.ruoyi.common.annotation.DataSource;
import com.ruoyi.common.utils.StringUtils;
import com.ruoyi.framework.datasource.DynamicDataSourceContextHolder;
/**
* 多数据源处理
*
*/
@Aspect
@Order(1)
@Component
public class DataSourceAspect
{
protected Logger logger = LoggerFactory.getLogger(getClass());
@Pointcut("@annotation(com.ruoyi.common.annotation.DataSource)"
+ "|| @within(com.ruoyi.common.annotation.DataSource)")
public void dsPointCut()
{
}
@Around("dsPointCut()")
public Object around(ProceedingJoinPoint point) throws Throwable
{
DataSource dataSource = getDataSource(point);
if (StringUtils.isNotNull(dataSource))
{
DynamicDataSourceContextHolder.setDataSourceType(dataSource.value().name());
}
try
{
return point.proceed();
}
finally
{
// 销毁数据源 在执行方法之后
DynamicDataSourceContextHolder.clearDataSourceType();
}
}
/**
* 获取需要切换的数据源
*/
public DataSource getDataSource(ProceedingJoinPoint point)
{
MethodSignature signature = (MethodSignature) point.getSignature();
DataSource dataSource = AnnotationUtils.findAnnotation(signature.getMethod(), DataSource.class);
if (Objects.nonNull(dataSource))
{
return dataSource;
}
return AnnotationUtils.findAnnotation(signature.getDeclaringType(), DataSource.class);
}
}
7. DynamicDataSource.java (动态数据源)
import java.util.Map;
import javax.sql.DataSource;
import org.springframework.jdbc.datasource.lookup.AbstractRoutingDataSource;
/**
* 动态数据源
*
*/
public class DynamicDataSource extends AbstractRoutingDataSource
{
public DynamicDataSource(DataSource defaultTargetDataSource, Map<Object, Object> targetDataSources)
{
super.setDefaultTargetDataSource(defaultTargetDataSource);
super.setTargetDataSources(targetDataSources);
super.afterPropertiesSet();
}
@Override
protected Object determineCurrentLookupKey()
{
return DynamicDataSourceContextHolder.getDataSourceType();
}
}
8. DynamicDataSourceContextHolder.java (数据源切换处理)
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
/**
* 数据源切换处理
*
*/
public class DynamicDataSourceContextHolder
{
public static final Logger log = LoggerFactory.getLogger(DynamicDataSourceContextHolder.class);
/**
* 使用ThreadLocal维护变量,ThreadLocal为每个使用该变量的线程提供独立的变量副本,
* 所以每一个线程都可以独立地改变自己的副本,而不会影响其它线程所对应的副本。
*/
private static final ThreadLocal<String> CONTEXT_HOLDER = new ThreadLocal<>();
/**
* 设置数据源的变量
*/
public static void setDataSourceType(String dsType)
{
log.info("切换到{}数据源", dsType);
CONTEXT_HOLDER.set(dsType);
}
/**
* 获得数据源的变量
*/
public static String getDataSourceType()
{
return CONTEXT_HOLDER.get();
}
/**
* 清空数据源变量
*/
public static void clearDataSourceType()
{
CONTEXT_HOLDER.remove();
}
}
9. 测试- 在controller或者在service方法上贴上切面注解 @DataSource(value = DataSourceType.SLAVE)
@DataSource(value = DataSourceType.SLAVE)
@Override
public int insertZmUser(ZmUser zmUser) {
zmUser.setCreateTime(DateUtils.getNowDate());
zmUser.setUpdateTime(DateUtils.getNowDate());
return zmUserMapper.insertZmUser(zmUser);
}
10. 对于特殊情况可以通过DynamicDataSourceContextHolder手动实现数据源切换
public List<ZmUser> selectUserList(ZmUser zmUser){
// 切换到从库
DynamicDataSourceContextHolder.setDataSourceType(DataSourceType.SLAVE.name());
List<ZmUser> userList = zmUserMapper.selectZmUserList(zmUser);
DynamicDataSourceContextHolder.clearDataSourceType();
return userList;
}