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);
    }

spring boot使用aop实现多数据源动态切换 springboot如何切换数据源_mysql

 

spring boot使用aop实现多数据源动态切换 springboot如何切换数据源_mysql_02


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;
    }