com.github.trang.druid.autoconfigure.DruidDataSourceInitializerAutoConfiguration Maven / Gradle / Ivy
package com.github.trang.druid.autoconfigure;
import com.github.trang.druid.autoconfigure.datasource.init.DruidDataSourceInitializer;
import org.springframework.boot.autoconfigure.AutoConfigureAfter;
import org.springframework.boot.autoconfigure.condition.ConditionalOnBean;
import org.springframework.boot.autoconfigure.condition.ConditionalOnMissingBean;
import org.springframework.boot.autoconfigure.jdbc.DataSourceAutoConfiguration;
import org.springframework.boot.autoconfigure.jdbc.DataSourceProperties;
import org.springframework.context.ApplicationContext;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import javax.sql.DataSource;
/**
* 支持数据源初始化时执行 SQL
*
* 照搬自 #{@link org.springframework.boot.autoconfigure.jdbc.DataSourceInitializer}
*
* 在多数据源场景下，#{@link DataSourceAutoConfiguration} 会报 #{@code DataSource} 和
* #{@code DruidDataSourceInitializer} 的循环依赖，目前的解决办法是排除 #{@link DataSourceAutoConfiguration}，
* 但是这样一来，Spring Boot 在数据源初始化时执行 SQL 的特性会被移除，此类是为了保留该特性
*
* @author trang
*/
@Configuration
@AutoConfigureAfter(DataSourceAutoConfiguration.class)
@ConditionalOnBean(DataSource.class)
public class DruidDataSourceInitializerAutoConfiguration {
@Bean
@ConditionalOnMissingBean(
type = "org.springframework.boot.autoconfigure.jdbc.DataSourceInitializer",
value = DruidDataSourceInitializer.class)
public DruidDataSourceInitializer dataSourceInitializer(DataSourceProperties properties,
ApplicationContext applicationContext) {
return new DruidDataSourceInitializer(properties, applicationContext);
}
}