Nacos配置中心动态刷新数据源

前言

因为项目需要，需要在项目运行过程中能够动态修改数据源（即：数据源的热更新）。这里以com.alibaba.druid.pool.DruidDataSource数据源为例

第一步：重写DruidAbstractDataSource类

这里为什么要重写这个类：因为DruidDataSource数据源在初始化后，就不允许再重新设置数据库的url和userName

public void setUrl(String jdbcUrl) {
    
    if (StringUtils.equals(this.jdbcUrl, jdbcUrl)) {
    
      return;
    }
    // 重写的时候，需要将这个判断注释掉，否则会报错
    // if (inited) {
    
    // throw new UnsupportedOperationException();
    // }
 
    if (jdbcUrl != null) {
    
      jdbcUrl = jdbcUrl.trim();
    }
 
    this.jdbcUrl = jdbcUrl;
 
    // if (jdbcUrl.startsWith(ConfigFilter.URL_PREFIX)) {
    
    // this.filters.add(new ConfigFilter());
    // }
  }
 
  public void setUsername(String username) {
    
    if (StringUtils.equals(this.username, username)) {
    
      return;
    }
		// 重写的时候，需要将这个判断注释掉，否则会报错
    // if (inited) {
    
    // throw new UnsupportedOperationException();
    // }
 
    this.username = username;
  }

重写的时候包路径不能变，只有这样类加载的时候才会优先加载重写后的类

第二步：配置动态获取nacos配置信息

package com.easyshop.config;

import com.alibaba.druid.pool.DruidDataSource;
import lombok.Data;
import lombok.extern.slf4j.Slf4j;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.cloud.context.config.annotation.RefreshScope;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;

/** * * 描述：如果不使用代码手动初始化DataSource的话 */
@Slf4j
@Configuration
@RefreshScope
@Data
public class DruidConfiguration
{
    
    @Value("${spring.datasource.url}")
    private String dbUrl;

    @Value("${spring.datasource.username}")
    private String username;

    @Value("${spring.datasource.password}")
    private String password;

    @Value("${spring.datasource.driver-class-name}")
    private String driverClassName;

    // @Value("${spring.datasource.initialSize}")
    // private int initialSize;
    //
    // @Value("${spring.datasource.minIdle}")
    // private int minIdle;
    //
    // @Value("${spring.datasource.maxActive}")
    // private int maxActive;
    //
    // @Value("${spring.datasource.maxWait}")
    // private int maxWait;
    //
    // @Value("${spring.datasource.timeBetweenEvictionRunsMillis}")
    // private int timeBetweenEvictionRunsMillis;
    //
    // @Value("${spring.datasource.minEvictableIdleTimeMillis}")
    // private int minEvictableIdleTimeMillis;
    //
    // @Value("${spring.datasource.validationQuery}")
    // private String validationQuery;
    //
    // @Value("${spring.datasource.testWhileIdle}")
    // private boolean testWhileIdle;
    //
    // @Value("${spring.datasource.testOnBorrow}")
    // private boolean testOnBorrow;
    //
    // @Value("${spring.datasource.testOnReturn}")
    // private boolean testOnReturn;
    //
    // @Value("${spring.datasource.poolPreparedStatements}")
    // private boolean poolPreparedStatements;
    //
    // @Value("${spring.datasource.maxPoolPreparedStatementPerConnectionSize}")
    // private int maxPoolPreparedStatementPerConnectionSize;
    //
    // @Value("${spring.datasource.filters}")
    // private String filters;
    //
    // @Value("${spring.datasource.connectionProperties}")
    // private String connectionProperties;
    //
    // @Value("${spring.datasource.useGlobalDataSourceStat}")
    // private boolean useGlobalDataSourceStat;

    @Bean
    @RefreshScope
    public DruidDataSource dataSource()
    {
    
        DruidDataSource datasource = new DruidDataSource();
        datasource.setUrl(this.dbUrl);
        datasource.setUsername(username);
        datasource.setPassword(password);
        datasource.setDriverClassName(driverClassName);

        //configuration
        // datasource.setInitialSize(initialSize);
        // datasource.setMinIdle(minIdle);
        // datasource.setMaxActive(maxActive);
        // datasource.setMaxWait(maxWait);
        // datasource.setTimeBetweenEvictionRunsMillis(timeBetweenEvictionRunsMillis);
        // datasource.setMinEvictableIdleTimeMillis(minEvictableIdleTimeMillis);
        // datasource.setValidationQuery(validationQuery);
        // datasource.setTestWhileIdle(testWhileIdle);
        // datasource.setTestOnBorrow(testOnBorrow);
        // datasource.setTestOnReturn(testOnReturn);
        // datasource.setPoolPreparedStatements(poolPreparedStatements);
        // datasource.setMaxPoolPreparedStatementPerConnectionSize(maxPoolPreparedStatementPerConnectionSize);
        // datasource.setUseGlobalDataSourceStat(useGlobalDataSourceStat);
        // try
        // {
    
        // datasource.setFilters(filters);
        // }
        // catch (SQLException e)
        // {
    
        // log.error("druid configuration initialization filter: " + e);
        // }
        // datasource.setConnectionProperties(connectionProperties);
        return datasource;
    }
}

这里要注意增加@RefreshScope注解

第三步：手动刷新数据源

 @Autowired
 private DruidConfiguration druidConfiguration;

 @GetMapping("/refresh")
 public String refresh() throws SQLException {
    
     DruidDataSource master = SpringUtils.getBean("dataSource");
     master.setUrl(druidConfiguration.getDbUrl());
     master.setUsername(druidConfiguration.getUsername());
     master.setPassword(druidConfiguration.getPassword());
     master.setDriverClassName(druidConfiguration.getDriverClassName());
     master.restart();
     return druidConfiguration.getDbUrl();
 }

到此这篇关于SpringBoot集成nacos动态刷新数据源的实现示例的文章就介绍到这了