Java使用Memcached

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这些天在设计SNA的架构，接触了一些远程缓存、集群、session复制等的东西，以前做企业应用的时候感觉作用不大，现在设计面对internet的系统架构时就非常有用了，而且在调试后看到压力测试的情况还是比较爽的。
在缓存的选择上有过很多的思考，虽然说memcached结合java在序列化上性能不怎么样，不过也没有更好的集群环境下的缓存解决方案了，就选择了memcached。本来计划等公司买的服务器到位装个linux再来研究memcached，但这两天在找到了一个windows下的Memcached版本，就动手开始调整现有的框架了。

windows下的Server端很简单，不用安装，双击运行后默认服务端口是11211，没有试着去更改端口，因为反正以后会用unix版本，到时再记录安装步骤。下载客户端的java API包，接口非常简单，参考API手册上就有现成的例子。

目标，对旧框架缓存部分进行改造：
1、缓存工具类
2、hibernate的provider
3、用缓存实现session机制

今天先研究研究缓存工具类的改造，在旧框架中部分函数用了ehcache对执行结果进行了缓存处理，现在目标是提供一个缓存工具类，在配置文件中配置使用哪种缓存（memcached或ehcached），使其它程序对具体的缓存不依赖，同时使用AOP方式来对方法执行结果进行缓存。
首先是工具类的实现：
在Spring中配置

Java代码

<bean id="cacheManager"
class="org.springframework.cache.ehcache.EhCacheManagerFactoryBean">
<property name="configLocation">
<value>classpath:ehcache.xml</value>
</property>
</bean>
<bean id="localCache"
class="org.springframework.cache.ehcache.EhCacheFactoryBean">
<property name="cacheManager" ref="cacheManager" />
<property name="cacheName"
value="×××.cache.LOCAL_CACHE" />
</bean>
<bean id="cacheService"
class="×××.core.cache.CacheService" init-method="init" destroy-method="destory">
<property name="cacheServerList" value="${cache.servers}"/>
<property name="cacheServerWeights" value="${cache.cacheServerWeights}"/>
<property name="cacheCluster" value="${cache.cluster}"/>
<property name="localCache" ref="localCache"/>
</bean>

在properties文件中配置${cache.servers} ${cache.cacheServerWeights} ${cache.cluster}
具体工具类的代码

Java代码

/**
* @author Marc
*
*/
public class CacheService {
private Log logger = LogFactory.getLog(getClass());
private Cache localCache;
String cacheServerList;
String cacheServerWeights;
boolean cacheCluster = false;
int initialConnections = 10;
int minSpareConnections = 5;
int maxSpareConnections = 50;
long maxIdleTime = 1000 * 60 * 30; // 30 minutes
long maxBusyTime = 1000 * 60 * 5; // 5 minutes
long maintThreadSleep = 1000 * 5; // 5 seconds
int socketTimeOut = 1000 * 3; // 3 seconds to block on reads
int socketConnectTO = 1000 * 3; // 3 seconds to block on initial
// connections. If 0, then will use blocking
// connect (default)
boolean failover = false; // turn off auto-failover in event of server
// down
boolean nagleAlg = false; // turn off Nagle's algorithm on all sockets in
// pool
MemCachedClient mc;
public CacheService(){
mc = new MemCachedClient();
mc.setCompressEnable(false);
}
/**
* 放入
*
*/
public void put(String key, Object obj) {
Assert.hasText(key);
Assert.notNull(obj);
Assert.notNull(localCache);
if (this.cacheCluster) {
mc.set(key, obj);
} else {
Element element = new Element(key, (Serializable) obj);
localCache.put(element);
}
}
/**
* 删除
*/
public void remove(String key){
Assert.hasText(key);
Assert.notNull(localCache);
if (this.cacheCluster) {
mc.delete(key);
}else{
localCache.remove(key);
}
}
/**
* 得到
*/
public Object get(String key) {
Assert.hasText(key);
Assert.notNull(localCache);
Object rt = null;
if (this.cacheCluster) {
rt = mc.get(key);
} else {
Element element = null;
try {
element = localCache.get(key);
} catch (CacheException cacheException) {
throw new DataRetrievalFailureException("Cache failure: "
+ cacheException.getMessage());
}
if(element != null)
rt = element.getValue();
}
return rt;
}
/**
* 判断是否存在
*
*/
public boolean exist(String key){
Assert.hasText(key);
Assert.notNull(localCache);
if (this.cacheCluster) {
return mc.keyExists(key);
}else{
return this.localCache.isKeyInCache(key);
}
}
private void init() {
if (this.cacheCluster) {
String[] serverlist = cacheServerList.split(",");
Integer[] weights = this.split(cacheServerWeights);
// initialize the pool for memcache servers
SockIOPool pool = SockIOPool.getInstance();
pool.setServers(serverlist);
pool.setWeights(weights);
pool.setInitConn(initialConnections);
pool.setMinConn(minSpareConnections);
pool.setMaxConn(maxSpareConnections);
pool.setMaxIdle(maxIdleTime);
pool.setMaxBusyTime(maxBusyTime);
pool.setMaintSleep(maintThreadSleep);
pool.setSocketTO(socketTimeOut);
pool.setSocketConnectTO(socketConnectTO);
pool.setNagle(nagleAlg);
pool.setHashingAlg(SockIOPool.NEW_COMPAT_HASH);
pool.initialize();
logger.info("初始化memcached pool!");
}
}
private void destory() {
if (this.cacheCluster) {
SockIOPool.getInstance().shutDown();
}
}
}

然后实现函数的AOP拦截类，用来在函数执行前返回缓存内容

Java代码

public class CachingInterceptor implements MethodInterceptor {
private CacheService cacheService;
private String cacheKey;
public void setCacheKey(String cacheKey) {
this.cacheKey = cacheKey;
}
public void setCacheService(CacheService cacheService) {
this.cacheService = cacheService;
}
public Object invoke(MethodInvocation invocation) throws Throwable {
Object result = cacheService.get(cacheKey);
//如果函数返回结果不在Cache中,执行函数并将结果放入Cache
if (result == null) {
result = invocation.proceed();
cacheService.put(cacheKey,result);
}
return result;
}
}

Spring的AOP配置如下：

Java代码

<aop:config proxy-target-class="true">
<aop:advisor
pointcut="execution(* ×××.PoiService.getOne(..))"
advice-ref="PoiServiceCachingAdvice" />
</aop:config>
<bean id="BasPoiServiceCachingAdvice"
class="×××.core.cache.CachingInterceptor">
<property name="cacheKey" value="PoiService" />
<property name="cacheService" ref="cacheService" />
</bean>

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