分布式EHCACHE系统,如何实现缓存数据同步?
这也是最常用的方式,配置简单,关键一点,各EHCACHE的节点配置都是一样的
例子:
spring 配置中调用的ehcache文件
<bean
id="cacheManager"
class="org.springframework.cache.ehcache.EhCacheManagerFactoryBean">
<property
name="configLocation">
<value>classpath:ehcache_mc.xml</value>
</property>
</bean>
<bean id="userCache"
class="org.springframework.cache.ehcache.EhCacheFactoryBean">
<property
name="cacheManager">
<ref local="cacheManager"/>
</property>
<property
name="cacheName">
<value>userCache</value>
</property>
</bean> |
ehcache_mc.xml:
<cache name="userCache"
maxElementsInMemory="10000"
maxElementsOnDisk="0"
eternal="true"
overflowToDisk="true"
diskSpoolBufferSizeMB="20"
memoryStoreEvictionPolicy="LFU"
transactionalMode="off">
<cacheEventListenerFactory
class="net.sf.ehcache.distribution.RMICacheReplicatorFactory"
properties="replicateAsynchronously=true, replicatePuts=true,
replicateUpdates=true,replicateUpdatesViaCopy= true,
replicateRemovals= true "
/>
<cacheEventListenerFactory
class="cn.com.gary.test.ehcache.EventFactory" />
<!-- 打印ehcache 动作日志 -->
</cache>
<cacheManagerPeerProviderFactory
class="net.sf.ehcache.distribution.RMICacheManagerPeerProviderFactory"
properties="peerDiscovery=automatic,
multicastGroupAddress=230.0.0.1,
multicastGroupPort=4446,timeToLive=255"/>
<cacheManagerPeerListenerFactory
class="net.sf.ehcache.distribution.RMICacheManagerPeerListenerFactory"/>
|
原理:
这样当缓存改变时,ehcache会向230.0.0.1端口4446发RMI UDP组播包
这种组播方式的缺陷:
EHCACHE的组播做得比较初级,功能只是基本实现(比如简单的一个HUB,接两台单网卡的服务器,互相之间组播同步就没问题),
对一些复杂的环境(比如多台服务器,每台服务器上多地址,尤其是集群,存在一个集群地址带多个物理机,每台物理机又带多个虚拟站的子地址),就容易出现问题.
究其原因, 组播/广播转发是一个很复杂的过程. 简单的说,
一个组播缺省只能在一个网段内传输,不能跨网段.
举个简单的例子,
PC机网卡的自动获取地址,还有WINDOWS里的网上邻居,都属于典型的广播服务,所以这些服务都是不能跨网段(跨路由)的,当然也不是完全不行,借助一些工具,比如CISCO路由器上的udp-broadcast
helper,或者微软的netBIOS on Tcp/ip,就可以实现.
我们自己安装一些软件时,也经常遇到比如"将网卡的广播转发打开"之类的操作.
而在多网卡的主机,或同一网卡多IP的主机上,尽管地址可能是一个网段内的,但其实地址间已经存在跳数了(hop),其实就是从一个地址向另一个地址跳.
这时广播/组播就容易被阻断.
比如:
我们自己的WINDOWS上装一个VMWARE虚拟机,尽管IP地址是一个网段的,但因为虚拟机采用的桥模式不是标准的网桥模式(也可能是需要配置一下,但说实话懒得研究VMWARE了),所以广播/组播也经常出现不通的情况.
更何况在一些云计算的环境,集群的分布往往是跨网段的,甚至是跨地域的.这时更难以依赖这种初级的组播同步.
总之,分布式集群架构,建议EHCACHE改为PEER-2-PEER的同步方式.
其实就是每个节点和其他n-1个节点都建立TCP的P2P PEER.
下面是一个3节点的ehcache分布式部署:
节点1:
spring 配置中调用的ehcache文件
<bean
id="cacheManager"
class="org.springframework.cache.ehcache.EhCacheManagerFactoryBean">
<property
name="configLocation">
<value>classpath:ehcache_p2p_40001.xml</value>
</property>
</bean>
<bean id="userCache"
class="org.springframework.cache.ehcache.EhCacheFactoryBean">
<property
name="cacheManager">
<ref local="cacheManager"/>
</property>
<property
name="cacheName">
<value>userCache</value>
</property>
</bean>
ehcache_p2p_40001.xml
<cache name="userCache"
maxElementsInMemory="10000"
maxElementsOnDisk="0"
eternal="true"
overflowToDisk="true"
diskSpoolBufferSizeMB="20"
memoryStoreEvictionPolicy="LFU"
transactionalMode="off">
<cacheEventListenerFactory
class="net.sf.ehcache.distribution.RMICacheReplicatorFactory"
properties="replicateAsynchronously=true, replicatePuts=true,
replicateUpdates=true,replicateUpdatesViaCopy= true,
replicateRemovals= true " />
<cacheEventListenerFactory
class="cn.com.dwsoft.test.ehcache.EventFactory"
/>
</cache>
<!--调用ehcache2的RMI-->
<cacheManagerPeerProviderFactory
class="net.sf.ehcache.distribution.RMICacheManagerPeerProviderFactory"
properties="peerDiscovery=manual,rmiUrls=//192.168.0.251:40002/userCache|//192.168.0.251:40003/userCache"/>
<!--RMI监听40001端口-->
<cacheManagerPeerListenerFactory
class="net.sf.ehcache.distribution.RMICacheManagerPeerListenerFactory"
properties="hostName=192.168.0.122,port=40001,socketTimeoutMillis=2000"/>
|
节点2:
spring 配置中调用的ehcache文件
<bean
id="cacheManager"
class="org.springframework.cache.ehcache.EhCacheManagerFactoryBean">
<property
name="configLocation">
<value>classpath:ehcache_p2p_40002.xml</value>
</property>
</bean>
<bean id="userCache"
class="org.springframework.cache.ehcache.EhCacheFactoryBean">
<property
name="cacheManager">
<ref local="cacheManager"/>
</property>
<property
name="cacheName">
<value>userCache</value>
</property>
</bean>
ehcache_p2p_40002.xml
<cache name="userCache"
maxElementsInMemory="10000"
maxElementsOnDisk="0"
eternal="true"
overflowToDisk="true"
diskSpoolBufferSizeMB="20"
memoryStoreEvictionPolicy="LFU"
transactionalMode="off">
<cacheEventListenerFactory
class="net.sf.ehcache.distribution.RMICacheReplicatorFactory"
properties="replicateAsynchronously=true, replicatePuts=true,
replicateUpdates=true,replicateUpdatesViaCopy= true,
replicateRemovals= true " />
<cacheEventListenerFactory
class="cn.com.dwsoft.test.ehcache.EventFactory"
/>
</cache>
<!--调用ehcache2的RMI-->
<cacheManagerPeerProviderFactory
class="net.sf.ehcache.distribution.RMICacheManagerPeerProviderFactory"
properties="peerDiscovery=manual,rmiUrls=//192.168.0.122:40001/userCache|//192.168.0.251:40003/userCache"/>
<!--RMI监听40001端口-->
<cacheManagerPeerListenerFactory
class="net.sf.ehcache.distribution.RMICacheManagerPeerListenerFactory"
properties="hostName=192.168.0.251,port=40002,socketTimeoutMillis=2000"/>
|
节点3:
spring 配置中调用的ehcache文件
<bean
id="cacheManager"
class="org.springframework.cache.ehcache.EhCacheManagerFactoryBean">
<property
name="configLocation">
<value>classpath:ehcache_p2p_40003.xml</value>
</property>
</bean>
<bean id="userCache"
class="org.springframework.cache.ehcache.EhCacheFactoryBean">
<property
name="cacheManager">
<ref local="cacheManager"/>
</property>
<property
name="cacheName">
<value>userCache</value>
</property>
</bean>
ehcache_p2p_40003.xml
<cache name="userCache"
maxElementsInMemory="10000"
maxElementsOnDisk="0"
eternal="true"
overflowToDisk="true"
diskSpoolBufferSizeMB="20"
memoryStoreEvictionPolicy="LFU"
transactionalMode="off">
<cacheEventListenerFactory
class="net.sf.ehcache.distribution.RMICacheReplicatorFactory"
properties="replicateAsynchronously=true, replicatePuts=true,
replicateUpdates=true,replicateUpdatesViaCopy= true,
replicateRemovals= true " />
<cacheEventListenerFactory
class="cn.com.dwsoft.test.ehcache.EventFactory"
/>
</cache>
<!--调用ehcache2的RMI-->
<cacheManagerPeerProviderFactory
class="net.sf.ehcache.distribution.RMICacheManagerPeerProviderFactory"
properties="peerDiscovery=manual,rmiUrls=//192.168.0.122:40001/userCache|//192.168.0.251:40002/userCache"/>
<!--RMI监听40001端口-->
<cacheManagerPeerListenerFactory
class="net.sf.ehcache.distribution.RMICacheManagerPeerListenerFactory"
properties="hostName=192.168.0.251,port=40003,socketTimeoutMillis=2000"/>
|
测试
节点1添加一条缓存条目
节点1日志:
2012-08-28 17:00:39,859 INFO
CustomActionSupport.getParameter(188)-/admin/inputEntry.do?
submit=提交&cachekey=mac1228&cachevalue=1228
2012-08-28 17:00:39,859 INFO
TestAction.inputEntry(97)-mac1228:1228
2012-08-28 17:00:39,875 INFO CacheEvent.log(65)-in
notifyElementPut[ key = mac1228, value=1228, version=1, hitCount=0,
CreationTime = 1346144439875, LastAccessTime = 1346144439875
]
2012-08-28 17:00:39,875DEBUG
ServletDispatcherResult.debug(57)-Forwarding to location /index.jsp
|
节点2日志:
2011-09-22 14:25:51,262 INFO
CacheEvent.log(65)-in notifyElementPut[ key = mac1228, value=1228,
version=1, hitCount=0, CreationTime = 1346144440000, LastAccessTime
= 1316672751253 ] |
节点3日志:
2011-09-22 14:25:51,198 INFO
CacheEvent.log(65)-in notifyElementPut[ key = mac1228, value=1228,
version=1, hitCount=0, CreationTime = 1346144440000, LastAccessTime
= 1316672751198 ] |
|
节点2添加一条缓存条目
节点1日志:
2012-08-28 16:54:55,890 INFO
CacheEvent.log(65)-in notifyElementPut[ key = mac25181904,
value=25181904, version=1, hitCount=0, CreationTime =
1316672407000, LastAccessTime = 1346144095890
] |
节点2日志:
2011-09-22 14:20:06,041 INFO
CustomActionSupport.getParameter(188)-/admin/inputEntry.do?
submit=提交&cachekey=mac25181904&cachevalue=25181904
2011-09-22 14:20:06,042 INFO
TestAction.inputEntry(97)-mac25181904:25181904
2011-09-22 14:20:06,050DEBUG
ServletDispatcherResult.debug(57)-Forwarding to location
/index.jsp |
节点3日志:
2011-09-22 14:20:06,568 INFO
CacheEvent.log(65)-in notifyElementPut[ key = mac25181904,
value=25181904, version=1, hitCount=0, CreationTime =
1316672407000, LastAccessTime = 1316672406568 ]
|
|
总结:
上面说了,组播方式同步不可靠.
P2P方式其实也存在不可靠的地方.这就是P2P要求每个节点的EHCACHE要指向其他的N-1个节点,
当在云环境,或集群域下, 多个子节点部署项目都是被自动发布的,这时很难做到不同节点有不同的配置,因为自动发布,配置往往都是相同的,这样P2P就很难实现.
总之,这种同步型应用是很难适应大规模分布式部署的,还是建议采用一些集中软件比如MEMCACHED.
加载中,请稍候......