随着数据量的增长以及业务的调整变更,我们需要选择合适的技术及存储引擎对数据进行归类,调整,达到高并发、秒响应、低延迟及可扩展对现有程序的改造升级
1.对于问题一,我们要采用oop to aop 的变成思维的转变,即通过切面来完成,尽量不改动原来的业务逻辑,尤其是之前的老系统,多分组,一个改动,可能导致几十个bug 的,横空出世,太太可怕了吧
2. 第二个问题就是兼容,略带框架思维,走配置化和开关,不仅可以起到有效的解耦,而且还可以做到有效的补偿,有问题及时解决
3. 总体方案 切面 + 配置化
1. xml 配置
<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xmlns:tx="http://www.springframework.org/schema/tx"
xsi:schemaLocation="http://www.springframework.org/schema/beans
http://www.springframework.org/schema/beans/spring-beans-3.0.xsd
http://www.springframework.org/schema/tx
http://www.springframework.org/schema/tx/spring-tx-2.5.xsd">
<bean id="parentDataSource" class="com.alibaba.druid.pool.DruidDataSource" destroy-method="close">
<property name="driverClassName" value="${jdbc.driverClassName}"/>
<property name="maxActive" value="${windBird.maxActive}"/>
<property name="initialSize" value="${windBird.initialSize}"/>
<property name="maxWait" value="${windBird.maxWait}"/>
<property name="minIdle" value="${windBird.minIdle}"/>
<property name="timeBetweenEvictionRunsMillis" value="${windBird.timeBetweenEvictionRunsMillis}"/>
<property name="minEvictableIdleTimeMillis" value="${windBird.minEvictableIdleTimeMillis}"/>
<property name="validationQuery" value="${windBird.validationQuery}"/>
<property name="testWhileIdle" value="${windBird.testWhileIdle}"/>
<property name="testOnBorrow" value="${windBird.testOnBorrow}"/>
<property name="testOnReturn" value="${windBird.testOnReturn}"/>
<property name="poolPreparedStatements" value="${windBird.poolPreparedStatements}"/>
<property name="maxOpenPreparedStatements" value="${windBird.maxOpenPreparedStatements}"/>
</bean>
<bean id="newDataSource" parent="parentDataSource">
<property name="url">
<value>${
jdbc_new.url}</value>
</property>
<property name="username">
<value>${
jdbc_new.username}</value>
</property>
<property name="password">
<value>${
jdbc_new.password}</value>
</property>
</bean>
<bean id="oldDataSource" parent="parentDataSource">
<property name="url">
<value>${
jdbc_old.url}</value>
</property>
<property name="username">
<value>${
jdbc_old.username}</value>
</property>
<property name="password">
<value>${
jdbc_old.password}</value>
</property>
</bean>
<!--构造一个动态数据源 -->
<bean id="enhanceDynamicDataSource" class="com.windBird.service.impl.dataSource.enhanceDynamicDataSource"></bean>
<!--添加一个拦截器 -->
<bean id="enhanceMapperInterceptor" class="com.windBird.service.impl.dataSource.EnhanceMapperInterceptor"></bean>
<bean id="sqlSessionFactoryTestDataSource" class="org.mybatis.spring.SqlSessionFactoryBean">
<property name="dataSource" ref="enhanceDynamicDataSource"/>
<property name="typeAliasesPackage" value="com.windBird.service.entity"/>
<property name="mapperLocations">
<list>
<value>classpath:/sqlmap/test/*Mapper.xml
classpath:/sqlmap/test/enhance/*Mapper.xml
2. 构造的动态数据源
package com.wind.bird.service.impl.dataSource;
import com.alibaba.druid.pool.DruidDataSource;
import org.springframework.jdbc.datasource.lookup.AbstractRoutingDataSource;
import javax.annotation.Resource;
import javax.sql.DataSource;
/**
* @author windbird
* @Date 2022/12/4 22:03
* @ClassName EnhanceDynamicDataSource
* @desc: 构造动态数据源
*/
public class EnhanceDynamicDataSource extends AbstractRoutingDataSource {
/**
* 仅仅历史dao层切mapper
*/
private static final ThreadLocal<Boolean> testReadMark = ThreadLocal.withInitial(() -> false);
public static void setTestReadMark(Boolean Value){
testReadMark.set(Value);
}
public static Boolean getTestReadMark(){
return testReadMark.get();
}