这篇文章给大家介绍springboot中怎么配置多数据源,内容非常详细,感兴趣的小伙伴们可以参考借鉴,希望对大家能有所帮助。
配置文件数据源读取
通过springboot的Envioment和Binder对象进行读取,无需手动声明DataSource的Bean
yml数据源配置格式如下:
spring: datasource: master: type: com.alibaba.druid.pool.DruidDataSource driverClassName: com.mysql.cj.jdbc.Driver url: jdbc:mysql://localhost:3306/main? useUnicode=true&characterEncoding=utf8&zeroDateTimeBehavior=convertToNull&serverTimezone=Asia/Shanghai username: root password: 11111 cluster: - key: db1 type: com.alibaba.druid.pool.DruidDataSource driverClassName: com.mysql.cj.jdbc.Driver url: jdbc:mysql://localhost:3306/haopanframetest_db1? useUnicode=true&characterEncoding=utf8&zeroDateTimeBehavior=convertToNull&serverTimezone=Asia/Shanghai username: root password: 11111 - key: db2 type: com.alibaba.druid.pool.DruidDataSource driverClassName: com.mysql.cj.jdbc.Driver url: jdbc:mysql://localhost:3306/haopanframetest_db2? useUnicode=true&characterEncoding=utf8&zeroDateTimeBehavior=convertToNull&serverTimezone=Asia/Shanghai username: root password: 11111
master为主数据库必须配置,cluster下的为从库,选择性配置
获取配置文件信息代码如下
@Autowiredprivate Environment env;@Autowiredprivate ApplicationContext applicationContext;private Binder binder; binder = Binder.get(env); List<Map> configs = binder.bind("spring.datasource.cluster", Bindable.listOf(Map.class)).get();for (int i = 0; i < configs.size(); i++) { config = configs.get(i); String key = ConvertOp.convert2String(config.get("key")); String type = ConvertOp.convert2String(config.get("type")); String driverClassName = ConvertOp.convert2String(config.get("driverClassName")); String url = ConvertOp.convert2String(config.get("url")); String username = ConvertOp.convert2String(config.get("username")); String password = ConvertOp.convert2String(config.get("password")); }
定义获取数据源的Service,具体项目中进行实现
public interface ExtraDataSourceService {List<DataSourceModel> getExtraDataSourc(); }
获取对应Service的所有实现类进行调用
private List<DataSourceModel> getExtraDataSource(){ List<DataSourceModel> dataSourceModelList = new ArrayList<>(); Map<String, ExtraDataSourceService> res = applicationContext.getBeansOfType(ExtraDataSourceService.class);for (Map.Entry en :res.entrySet()) { ExtraDataSourceService service = (ExtraDataSourceService)en.getValue(); dataSourceModelList.addAll(service.getExtraDataSourc()); }return dataSourceModelList; }
主要是用过继承类AbstractRoutingDataSource,重写setTargetDataSources/setDefaultTargetDataSource方法
// 创建数据源public boolean createDataSource(String key, String driveClass, String url, String username, String password, String databasetype) {try {try { // 排除连接不上的错误Class.forName(driveClass); DriverManager.getConnection(url, username, password);// 相当于连接数据库} catch (Exception e) {return false; }@SuppressWarnings("resource") DruidDataSource druidDataSource = new DruidDataSource(); druidDataSource.setName(key); druidDataSource.setDriverClassName(driveClass); druidDataSource.setUrl(url); druidDataSource.setUsername(username); druidDataSource.setPassword(password); druidDataSource.setInitialSize(1); //初始化时建立物理连接的个数。初始化发生在显示调用init方法,或者第一次getConnection时druidDataSource.setMaxActive(20); //最大连接池数量druidDataSource.setMaxWait(60000); //获取连接时最大等待时间,单位毫秒。当链接数已经达到了最大链接数的时候,应用如果还要获取链接就会出现等待的现象,等待链接释放并回到链接池,如果等待的时间过长就应该踢掉这个等待,不然应用很可能出现雪崩现象druidDataSource.setMinIdle(5); //最小连接池数量String validationQuery = "select 1 from dual"; druidDataSource.setTestOnBorrow(true); //申请连接时执行validationQuery检测连接是否有效,这里建议配置为TRUE,防止取到的连接不可用druidDataSource.setTestWhileIdle(true);//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。druidDataSource.setValidationQuery(validationQuery); //用来检测连接是否有效的sql,要求是一个查询语句。如果validationQuery为null,testOnBorrow、testOnReturn、testWhileIdle都不会起作用。druidDataSource.setFilters("stat");//属性类型是字符串,通过别名的方式配置扩展插件,常用的插件有:监控统计用的filter:stat日志用的filter:log4j防御sql注入的filter:walldruidDataSource.setTimeBetweenEvictionRunsMillis(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druidDataSource.setMinEvictableIdleTimeMillis(180000); //配置一个连接在池中最小生存的时间,单位是毫秒,这里配置为3分钟180000druidDataSource.setKeepAlive(true); //打开druid.keepAlive之后,当连接池空闲时,池中的minIdle数量以内的连接,空闲时间超过minEvictableIdleTimeMillis,则会执行keepAlive操作,即执行druid.validationQuery指定的查询SQL,一般为select * from dual,只要minEvictableIdleTimeMillis设置的小于防火墙切断连接时间,就可以保证当连接空闲时自动做保活检测,不会被防火墙切断druidDataSource.setRemoveAbandoned(true); //是否移除泄露的连接/超过时间限制是否回收。druidDataSource.setRemoveAbandonedTimeout(3600); //泄露连接的定义时间(要超过最大事务的处理时间);单位为秒。这里配置为1小时druidDataSource.setLogAbandoned(true); //移除泄露连接发生是是否记录日志druidDataSource.init();this.dynamicTargetDataSources.put(key, druidDataSource); setTargetDataSources(this.dynamicTargetDataSources);// 将map赋值给父类的TargetDataSourcessuper.afterPropertiesSet();// 将TargetDataSources中的连接信息放入resolvedDataSources管理log.info(key+"数据源初始化成功");//log.info(key+"数据源的概况:"+druidDataSource.dump());return true; } catch (Exception e) { log.error(e + "");return false; } }
定义注解
@Retention(RetentionPolicy.RUNTIME)@Target({ElementType.METHOD, ElementType.TYPE, ElementType.PARAMETER})@Documentedpublic @interface TargetDataSource {String value() default "master"; //该值即key值}
public class DBContextHolder {private static Logger log = LoggerFactory.getLogger(DBContextHolder.class);// 对当前线程的操作-线程安全的private static final ThreadLocal<String> contextHolder = new ThreadLocal<String>();// 调用此方法,切换数据源public static void setDataSource(String dataSource) { contextHolder.set(dataSource); log.info("已切换到数据源:{}",dataSource); }// 获取数据源public static String getDataSource() {return contextHolder.get(); }// 删除数据源public static void clearDataSource() { contextHolder.remove(); log.info("已切换到主数据源"); } }
方法的注解优先级高于类注解,一般用于Service的实现类
@Aspect@Component@Order(Ordered.HIGHEST_PRECEDENCE)public class DruidDBAspect {private static Logger logger = LoggerFactory.getLogger(DruidDBAspect.class);@Autowiredprivate DynamicDataSource dynamicDataSource;/** * 切面点 指定注解 * */@Pointcut("@annotation(com.haopan.frame.common.annotation.TargetDataSource) " +"|| @within(com.haopan.frame.common.annotation.TargetDataSource)")public void dataSourcePointCut() { }/** * 拦截方法指定为 dataSourcePointCut * */@Around("dataSourcePointCut()")public Object around(ProceedingJoinPoint point) throws Throwable { MethodSignature signature = (MethodSignature) point.getSignature(); Class targetClass = point.getTarget().getClass(); Method method = signature.getMethod(); TargetDataSource targetDataSource = (TargetDataSource)targetClass.getAnnotation(TargetDataSource.class); TargetDataSource methodDataSource = method.getAnnotation(TargetDataSource.class);if(targetDataSource != null || methodDataSource != null){ String value;if(methodDataSource != null){ value = methodDataSource.value(); }else { value = targetDataSource.value(); } DBContextHolder.setDataSource(value); logger.info("DB切换成功,切换至{}",value); }try {return point.proceed(); } finally { logger.info("清除DB切换"); DBContextHolder.clearDataSource(); } } }
开发过程中某个库的某个表做了拆分操作,相同的某一次数据库操作可能对应到不同的库,需要对方法级别进行精确拦截,可以定义一个业务层面的切面,规定每个方法必须第一个参数为dbName,根据具体业务找到对应的库传参
@Around("dataSourcePointCut()")public Object around(ProceedingJoinPoint point) throws Throwable { MethodSignature signature = (MethodSignature) point.getSignature(); Class targetClass = point.getTarget().getClass(); Method method = signature.getMethod(); ProjectDataSource targetDataSource = (ProjectDataSource)targetClass.getAnnotation(ProjectDataSource.class); ProjectDataSource methodDataSource = method.getAnnotation(ProjectDataSource.class); String value = "";if(targetDataSource != null || methodDataSource != null){//获取方法定义参数DefaultParameterNameDiscoverer discover = new DefaultParameterNameDiscoverer(); String[] parameterNames = discover.getParameterNames(method);//获取传入目标方法的参数Object[] args = point.getArgs();for (int i=0;i<parameterNames.length;i++){ String pName = parameterNames[i];if(pName.toLowerCase().equals("dbname")){ value = ConvertOp.convert2String(args[i]); } }if(!StringUtil.isEmpty(value)){ DBContextHolder.setDataSource(value); logger.info("DB切换成功,切换至{}",value); } }try {return point.proceed(); } finally {if(!StringUtil.isEmpty(value)){ logger.info("清除DB切换"); DBContextHolder.clearDataSource(); } } }
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