Java实现数据库的读写分离
Posted liujinhua
tags:
篇首语：本文由小常识网(cha138.com)小编为大家整理，主要介绍了Java实现数据库的读写分离相关的知识，希望对你有一定的参考价值。
引言
1、读写分离：可以通过Spring提供的AbstractRoutingDataSource类，重写determineCurrentLookupKey方法，实现动态切换数据源的功能；读写分离可以有效减轻写库的压力，又可以把查询数据的请求分发到不同读库；
2、写数据库：当调用insert、update、delete及一些实时数据用到的库；
3、读数据库：当调用select查询数据用到的库；
4、JaveWeb工程通过AbstractRoutingDataSource类实现读写分离；
一、jdbc.properties文件配置读写数据源
datasource.type=mysql
datasource.driverClassName=com.mysql.jdbc.Driver
datasource.username=root
#写库w.datasource.url=jdbc:mysql://127.0.0.1:3306/ddt?characterEncoding=utf-8w.datasource.password=write123
#读库r.datasource.url=jdbc:mysql://IP:3306/ddt?characterEncoding=utf-8r.datasource.password=read123
#连接池配置
c3p0.acquireIncrement=3
c3p0.acquireRetryAttempts=10
c3p0.acquireRetryDelay=1000
c3p0.initialPoolSize=20
c3p0.idleConnectionTestPeriod=3600
c3p0.testConnectionOnCheckout=true
c3p0.minPoolSize=10
c3p0.maxPoolSize=80
c3p0.maxStatements=100
c3p0.numHelperThreads=10
c3p0.maxIdleTime=10800
二、application.xml文件
<?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:jee="http://www.springframework.org/schema/jee"
xmlns:tx="http://www.springframework.org/schema/tx" xmlns:context="http://www.springframework.org/schema/context"
xmlns:aop="http://www.springframework.org/schema/aop" xmlns:mvc="http://www.springframework.org/schema/mvc"
xmlns:task="http://www.springframework.org/schema/task"
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-3.0.xsd
http://www.springframework.org/schema/jee
http://www.springframework.org/schema/jee/spring-jee-3.0.xsd
http://www.springframework.org/schema/context
http://www.springframework.org/schema/context/spring-context-3.0.xsd
http://www.springframework.org/schema/aop
http://www.springframework.org/schema/aop/spring-aop-3.0.xsd
http://www.springframework.org/schema/task
http://www.springframework.org/schema/task/spring-task-3.0.xsd"> <!-- 使用annotation 自动注册bean,并保证@Required,@Autowired的属性被注入 -->
<context:component-scan base-package="com.eb3">
<context:include-filter type="annotation" expression="org.springframework.stereotype.Service" />
<context:exclude-filter type="annotation" expression="org.springframework.stereotype.Controller" />
</context:component-scan>
<bean class="org.springframework.beans.factory.config.PreferencesPlaceholderConfigurer" >
<property name="ignoreResourceNotFound" value="true" />
<property name="properties" ref="configProperties" />
</bean>
<bean id="configProperties" class="org.springframework.beans.factory.config.PropertiesFactoryBean">
<property name="locations">
<list>
<value>classpath*:jdbc.properties</value>
</list>
</property>
</bean>
<context:property-placeholder location="classpath:jdbc.properties"/>
<!-- 定义Hibernate读数据源 -->
<bean id="dataSourceRead" class="com.mchange.v2.c3p0.ComboPooledDataSource"
destroy-method="close">
<property name="driverClass">
<value>${datasource.driverClassName}</value>
</property>
<property name="jdbcUrl">
<value>${r.datasource.url}</value>
</property>
<property name="user">
<value>${datasource.username}</value>
</property>
<property name="password">
<value>${r.datasource.password}</value>
</property>
<!--当连接池中的连接耗尽的时候c3p0一次同时获取的连接数。-->
<property name="acquireIncrement">
<value>${c3p0.acquireIncrement}</value>
</property>
<!--定义在从数据库获取新连接失败后重复尝试的次数。-->
<property name="acquireRetryAttempts">
<value>${c3p0.acquireRetryAttempts}</value>
</property>
<!--两次连接中间隔时间，单位毫秒。-->
<property name="acquireRetryDelay">
<value>${c3p0.acquireRetryDelay}</value>
</property>
<property name="initialPoolSize">
<value>${c3p0.initialPoolSize}</value>
</property>
<property name="testConnectionOnCheckout">
<value>${c3p0.testConnectionOnCheckout}</value>
</property>
<property name="minPoolSize">
<value>${c3p0.minPoolSize}</value>
</property>
<property name="maxPoolSize">
<value>${c3p0.maxPoolSize}</value>
</property>
<property name="maxIdleTime">
<value>${c3p0.maxIdleTime}</value>
</property>
<property name="idleConnectionTestPeriod">
<value>${c3p0.idleConnectionTestPeriod}</value>
</property>
<property name="maxStatements">
<value>${c3p0.maxStatements}</value>
</property>
<property name="numHelperThreads">
<value>${c3p0.numHelperThreads}</value>
</property>
</bean>
<!-- 定义Hibernate写数据源 -->
<bean id="dataSourceWrite" class="com.mchange.v2.c3p0.ComboPooledDataSource"
destroy-method="close">
<property name="driverClass">
<value>${datasource.driverClassName}</value>
</property>
<property name="jdbcUrl">
<value>${w.datasource.url}</value>
</property>
<property name="user">
<value>${datasource.username}</value>
</property>
<property name="password">
<value>${w.datasource.password}</value>
</property>
<!--当连接池中的连接耗尽的时候c3p0一次同时获取的连接数。-->
<property name="acquireIncrement">
<value>${c3p0.acquireIncrement}</value>
</property>
<!--定义在从数据库获取新连接失败后重复尝试的次数。-->
<property name="acquireRetryAttempts">
<value>${c3p0.acquireRetryAttempts}</value>
</property>
<!--两次连接中间隔时间，单位毫秒。-->
<property name="acquireRetryDelay">
<value>${c3p0.acquireRetryDelay}</value>
</property>
<property name="initialPoolSize">
<value>${c3p0.initialPoolSize}</value>
</property>
<property name="testConnectionOnCheckout">
<value>${c3p0.testConnectionOnCheckout}</value>
</property>
<property name="minPoolSize">
<value>${c3p0.minPoolSize}</value>
</property>
<property name="maxPoolSize">
<value>${c3p0.maxPoolSize}</value>
</property>
<property name="maxIdleTime">
<value>${c3p0.maxIdleTime}</value>
</property>
<property name="idleConnectionTestPeriod">
<value>${c3p0.idleConnectionTestPeriod}</value>
</property>
<property name="maxStatements">
<value>${c3p0.maxStatements}</value>
</property>
<property name="numHelperThreads">
<value>${c3p0.numHelperThreads}</value>
</property>
</bean>
<!-- 动态数据源 -->
<bean id="dynamicDataSource" class="com.eb3.ddt.DynamicDataSource">
<!-- 通过key-value关联数据源 -->
<property name="targetDataSources">
<map>
<entry value-ref="dataSourceWrite" key="dataSourceWrite"></entry>
<entry value-ref="dataSourceRead" key="dataSourceRead"></entry>
</map>
</property>
<property name="defaultTargetDataSource" ref="dataSourceWrite" />
</bean>
<!-- 设置sessionFactory -->
<bean id="sessionFactory"
class="org.springframework.orm.hibernate3.annotation.AnnotationSessionFactoryBean">
<!-- 依赖注入数据源，注入正是上文定义的dataSource -->
<property name="dataSource" ref="dynamicDataSource" />
<property name="packagesToScan" value="com.eb3.ddt.pojo,com.eb3.loan.pojo"/>
<!--定义Hibernate的SessionFactory的属性 -->
<property name="hibernateProperties">
<props>
<!-- 指定Hibernate的连接方言-->
<prop key="hibernate.dialect">
${hibernate.dialect}
</prop>
<prop key="hibernate.connection.autocommit">${hibernate.connection.autocommit}</prop>
<!-- 制定Hibernate是否打印SQL语句 -->
<prop key="hibernate.show_sql">${hibernate.show_sql}</prop>
<prop key="hibernate.format_sql">${hibernate.format_sql}</prop>
<!-- 设create(启动创建),create-drop(启动创建,退出删除),update(启动更新),validate(启动验证) -->
<prop key="hibernate.hbm2ddl.auto">${hibernate.hbm2ddl.auto}</prop>
<prop key="connection.characterEncoding">utf-8</prop>
<!-- 设置二级缓存 -->
<prop key="hibernate.cache.user_query_cache">${hibernate.cache.user_query_cache}</prop>
<prop key="hibernate.user_second_level_cache">${hibernate.user_second_level_cache}</prop>
<prop key="hibernate.cache.provider_class">${hibernate.cache.class}</prop>
<prop key="hibernate.cache.provider_configuration_file_resource_path">${hibernate.ehcache_config_file}</prop>
</props>
</property>
</bean>
<!-- 事务管理器配置,单数据源事务 -->
<bean id="transactionManager" class="org.springframework.orm.hibernate3.HibernateTransactionManager">
<property name="sessionFactory" ref="sessionFactory"/>
</bean>
<tx:advice id="txAdvice" transaction-manager="transactionManager">
<tx:attributes>
<tx:method name="save*" propagation="REQUIRED" rollback-for="Exception"/>
<tx:method name="add*" propagation="REQUIRED" rollback-for="Exception"/>
<tx:method name="delete*" propagation="REQUIRED" rollback-for="Exception"/>
<tx:method name="update*" propagation="REQUIRED" rollback-for="Exception"/>
<tx:method name="merge*" isolation="READ_COMMITTED" propagation="REQUIRED" rollback-for="Exception"/>
<tx:method name="get*" read-only="true"/>
<tx:method name="find*" read-only="true"/>
<tx:method name="list*" read-only="true"/>
<tx:method name="select*" read-only="true"/>
<tx:method name="*" propagation="REQUIRED" />
</tx:attributes>
</tx:advice>
<aop:config>
<aop:pointcut id="interceptorPointCuts" expression="execution(* com.eb3.*.service.*.*(..))" />
<aop:advisor advice-ref="txAdvice" pointcut-ref="interceptorPointCuts" />
</aop:config>
<aop:aspectj-autoproxy proxy-target-class="true" />
<!-- 定时器配置 task:[email protected]调度线程池的大小，调度线程在被调度任务完成前不会空闲task:executor/@pool-size：可以指定执行线程池的初始大小、最大大小
task:executor/@queue-capacity：等待执行的任务队列的容量 task:executor/@rejection-policy：当等待队已满时的策略，分为丢弃、由任务执行器直接运行等方式
@Async 异步任务时 task任务执行线程数 task:scheduler 和 task:executor 两个线程池同样起作用 没有异步注解时
task任务执行线程数只受task:scheduler的线程池大小影响 -->
<!-- 声明一个具有10个线程的池，每一个对象将获取同样的运行机会 -->
<task:scheduler id="scheduler" pool-size="10" />
<task:executor id="executor" keep-alive="3600" pool-size="100-300" queue-capacity="500" rejection-policy="CALLER_RUNS" />
<task:annotation-driven executor="executor" scheduler="scheduler" />
</beans>
三、继承AbstractRoutingDataSource类的动态数据源类DynamicDataSource
package com.eb3.ddt;
import org.springframework.jdbc.datasource.lookup.AbstractRoutingDataSource;
public class DynamicDataSource extends AbstractRoutingDataSource {
/**
* 重写determineCurrentLookupKey方法
*/
@Override
protected Object determineCurrentLookupKey() {
Object obj = DBHelper.getDbType();
return obj;
}
}
四、DBHelper工具类
package com.eb3.ddt;
import org.apache.commons.lang.StringUtils;
public class DBHelper {
private static ThreadLocal<String> dbContext = new ThreadLocal<String>();
// 写数据源标识
public final static String DB_WRITE = "dataSourceWrite";
// 读数据源标识
public final static String DB_READ = "dataSourceRead";
/**
* 获取数据源类型，即是写数据源，还是读数据源
*
* @return
*/
public static String getDbType() {
String db_type = dbContext.get();
if (StringUtils.isEmpty(db_type)) {
// 默认是写数据源
db_type = DB_WRITE;
}
return db_type;
}
/**
* 设置该线程的数据源类型
*
* @param str
*/
public static void setDbType(String str) {
dbContext.set(str);
}
}
五、服务层调用
/*@Aspect 此注解会影响数据源切换，运行代码得知不加的话会先执行DynamicDataSource里的determineCurrentLookupKey方法，后执行Service层里DBHelper.setDbType()方法，导致数据源切换失败！*/
@Aspect
@Component("userService")public class UserServiceImpl extends BaseServiceImpl<User, User, Integer> implements UserService {
@Resource
private UserDao userDao;
@Override
protected BaseDao<User, Integer> getDao() {
return this.userDao;
}
@Override
public void save(User user) {
DBHelper.setDbType(DBHelper.DB_WRITE); // 写库 (向数据库中写)
this.userDao.save(user);
}
@Override
public User findByUserName(String username) {
DBHelper.setDbType(DBHelper.DB_READ); // 读库 (从数据库中向外读)
List<User> userList = this.userDao.findBy("username", username);
return CollectionUtils.isNotEmpty(userList) ? userList.get(0) : null;
}
}
以上是关于Java实现数据库的读写分离的主要内容，如果未能解决你的问题，请参考以下文章