标签：block 定义 logs oca over data setdaemon com packet
在第六章《路由表》中，客户端进行会话时，首先要获取对方的Session实例。获取Session实例的方法，是先查找本地路由表，若找不到，则通过路由表中的缓存数据，由定位器获取。
路由表中的缓存，如下：
public RoutingTableImpl() { super("Routing table"); serversCache = CacheFactory.createCache(S2S_CACHE_NAME); componentsCache = CacheFactory.createCache(COMPONENT_CACHE_NAME); usersCache = CacheFactory.createCache(C2S_CACHE_NAME); anonymousUsersCache = CacheFactory.createCache(ANONYMOUS_C2S_CACHE_NAME); usersSessions = CacheFactory.createCache(C2S_SESSION_NAME); localRoutingTable = new LocalRoutingTable(); }
这些缓存中，存储了整个集群内的所有Session信息。Openfire实现了对集群的支持接口，可能通过插件的形式构建集群。具体如何实现，下面来分析。本文使用的集群插件为Hazelcast。
1、interface：
RemoteSessionLocator ----> Session远程定位器，用于从集群中获取Session
ClusterEventListener ----> 监听集群加入、离开事件
CacheFactoryStrategy ----> 缓存策略接口
2、class：
ClusterManager ----> 集群管理类，管理自身而非集群。集群内的Master、缓存同步等由插件处理
CacheFactory ----> 缓存工厂类
DefaultLocalCacheStrategy ----> 本地缓存策略，实现CacheFactoryStrategy接口
ClusteredCacheFactory ----> 集群缓存策略，实现CacheFactoryStrategy接口
// 插件启动 initializePlugin()：ClusterManager.startup(); // 插件销毁 destroyPlugin()：ClusterManager.shutdown();
CluterManager中提供了集群事件的处理方法，主要如下两个队列进行：
private static Queue<ClusterEventListener> listeners = new ConcurrentLinkedQueue<>(); private static BlockingQueue<Event> events = new LinkedBlockingQueue<>(10000);
listeners：用于通知所有注册了ClusterEventListener事件的组件
events：用于存储集群中所有设备进、出集群的事件
并相应的提供了如下几个方法，用于操作这两个队列：
public static void fireJoinedCluster(byte[] nodeID, boolean asynchronous) { try { Event event = new Event(EventType.joined_cluster, nodeID); events.put(event); if (!asynchronous) { while (!event.isProcessed()) { Thread.sleep(50); } } } catch (InterruptedException e) { // Should never happen Log.error(e.getMessage(), e); } } public static void fireLeftCluster(byte[] nodeID) { try { Event event = new Event(EventType.left_cluster, nodeID); events.put(event); } catch (InterruptedException e) { // Should never happen Log.error(e.getMessage(), e); } }
public static void addListener(ClusterEventListener listener) { if (listener == null) { throw new NullPointerException(); } listeners.add(listener); } public static void removeListener(ClusterEventListener listener) { listeners.remove(listener); }
集群的启动方法
public static synchronized void startup() { if (isClusteringEnabled() && !isClusteringStarted()) { initEventDispatcher(); CacheFactory.startClustering(); } }
上面代码中， initEventDispatcher()方法，启动一个线程，根据events事件队列，完成事件调度。
private static void initEventDispatcher() { if (dispatcher == null || !dispatcher.isAlive()) { dispatcher = new Thread("ClusterManager events dispatcher") { @Override public void run() { // exit thread if/when clustering is disabled while (ClusterManager.isClusteringEnabled()) { try { Event event = events.take(); EventType eventType = event.getType(); // Make sure that CacheFactory is getting this events first (to update cache structure) if (event.getNodeID() == null) { // Replace standalone caches with clustered caches and migrate data if (eventType == EventType.joined_cluster) { CacheFactory.joinedCluster(); } else if (eventType == EventType.left_cluster) { CacheFactory.leftCluster(); } } // Now notify rest of the listeners for (ClusterEventListener listener : listeners) { try { switch (eventType) { case joined_cluster: { if (event.getNodeID() == null) { listener.joinedCluster(); } else { listener.joinedCluster(event.getNodeID()); } break; } case left_cluster: { if (event.getNodeID() == null) { listener.leftCluster(); } else { listener.leftCluster(event.getNodeID()); } break; } case marked_senior_cluster_member: { listener.markedAsSeniorClusterMember(); break; } default: break; } } catch (Exception e) { Log.error(e.getMessage(), e); } } // Mark event as processed event.setProcessed(true); } catch (Exception e) { Log.warn(e.getMessage(), e); } } } }; dispatcher.setDaemon(true); dispatcher.start(); } }
集群的关闭方法：
public static synchronized void shutdown() { if (isClusteringStarted()) { Log.debug("ClusterManager: Shutting down clustered cache service."); CacheFactory.stopClustering(); } }
由上过程可以看出，集群功能的具体实现，主要集中CacheFactory类中。
private static Map<String, Cache> caches = new ConcurrentHashMap<>();
通过调用指定的缓存策略构造缓存，并存入队列中：
@SuppressWarnings("unchecked")
public static synchronized <T extends Cache> T createCache(String name) {
T cache = (T) caches.get(name);
if (cache != null) {
return cache;
}
cache = (T) cacheFactoryStrategy.createCache(name);
log.info("Created cache [" + cacheFactoryStrategy.getClass().getName() + "] for " + name);
return wrapCache(cache, name);
}
Openfire定义的缓存策略有两种，本地缓存、集群缓存。这两种缓存策略对应的类名由Openfire预先定好。本地缓存由Openfire自身实现，集群缓存由集群插件按定好的类名规范实现。
两种缓存机制的类名如下：
static { localCacheFactoryClass = JiveGlobals.getProperty(LOCAL_CACHE_PROPERTY_NAME, "org.jivesoftware.util.cache.DefaultLocalCacheStrategy"); clusteredCacheFactoryClass = JiveGlobals.getProperty(CLUSTERED_CACHE_PROPERTY_NAME, "org.jivesoftware.openfire.plugin.util.cache.ClusteredCacheFactory"); }
无集群的情况，使用本地缓存：
public static synchronized void initialize() throws InitializationException { try { localCacheFactoryStrategy = (CacheFactoryStrategy) Class.forName(localCacheFactoryClass).newInstance(); cacheFactoryStrategy = localCacheFactoryStrategy; } catch (Exception e) { log.error("Failed to instantiate local cache factory strategy: " + localCacheFactoryClass, e); throw new InitializationException(e); } }
当加入集群时，切换为集群缓存：
@SuppressWarnings("unchecked")
public static synchronized void joinedCluster() {
cacheFactoryStrategy = clusteredCacheFactoryStrategy;
// Loop through local caches and switch them to clustered cache (copy content)
for (Cache cache : getAllCaches()) {
// skip local-only caches
if (localOnly.contains(cache.getName())) continue;
CacheWrapper cacheWrapper = ((CacheWrapper) cache);
Cache clusteredCache = cacheFactoryStrategy.createCache(cacheWrapper.getName());
clusteredCache.putAll(cache);
cacheWrapper.setWrappedCache(clusteredCache);
}
clusteringStarting = false;
clusteringStarted = true;
log.info("Clustering started; cache migration complete");
}
切换的方法是将本地缓存使用集群缓存策略重新生成一次，这时，本地的缓存将会被同步到集群中的各个机器上。
当离开集群时，又会切换为本地缓存：
@SuppressWarnings("unchecked")
public static synchronized void leftCluster() {
clusteringStarted = false;
cacheFactoryStrategy = localCacheFactoryStrategy;
// Loop through clustered caches and change them to local caches (copy content)
for (Cache cache : getAllCaches()) {
// skip local-only caches
if (localOnly.contains(cache.getName())) continue;
CacheWrapper cacheWrapper = ((CacheWrapper) cache);
Cache standaloneCache = cacheFactoryStrategy.createCache(cacheWrapper.getName());
standaloneCache.putAll(cache);
cacheWrapper.setWrappedCache(standaloneCache);
}
log.info("Clustering stopped; cache migration complete");
}
集群缓存策略，是Openfire与集群组件的过渡层。由Openfire制定了接口规范CacheFactoryStrategy，且包名必须为org.jivesoftware.openfire.plugin.util.cache.ClusteredCacheFactory，其中的方法，由具体的集群插件来完成。
集群缓存的创建：
public Cache createCache(String name) { // Check if cluster is being started up while (state == State.starting) { // Wait until cluster is fully started (or failed) try { Thread.sleep(250); } catch (InterruptedException e) { // Ignore } } if (state == State.stopped) { throw new IllegalStateException("Cannot create clustered cache when not in a cluster"); } return new ClusteredCache(name, hazelcast.getMap(name)); }
其中，CluteredCache对象的生成，是实现数据同步的关键：
return new ClusteredCache(name, hazelcast.getMap(name));
表明该缓存队列是Hazelcast中定义的，当队列发生变更时，实际上是更新了Hazelcast中的内容。
启动集群的方法
public boolean startCluster() { state = State.starting; // Set the serialization strategy to use for transmitting objects between node clusters serializationStrategy = ExternalizableUtil.getInstance().getStrategy(); ExternalizableUtil.getInstance().setStrategy(new ClusterExternalizableUtil()); // Set session locator to use when in a cluster XMPPServer.getInstance().setRemoteSessionLocator(new RemoteSessionLocator()); // Set packet router to use to deliver packets to remote cluster nodes XMPPServer.getInstance().getRoutingTable().setRemotePacketRouter(new ClusterPacketRouter()); ClassLoader oldLoader = null; // Store previous class loader (in case we change it) oldLoader = Thread.currentThread().getContextClassLoader(); ClassLoader loader = new ClusterClassLoader(); Thread.currentThread().setContextClassLoader(loader); int retry = 0; do { try { Config config = new ClasspathXmlConfig(HAZELCAST_CONFIG_FILE); config.setInstanceName("openfire"); config.setClassLoader(loader); if (JMXManager.isEnabled() && HAZELCAST_JMX_ENABLED) { config.setProperty("hazelcast.jmx", "true"); config.setProperty("hazelcast.jmx.detailed", "true"); } hazelcast = Hazelcast.newHazelcastInstance(config); cluster = hazelcast.getCluster(); // Update the running state of the cluster state = cluster != null ? State.started : State.stopped; // Set the ID of this cluster node XMPPServer.getInstance().setNodeID(NodeID.getInstance(getClusterMemberID())); // CacheFactory is now using clustered caches. We can add our listeners. clusterListener = new ClusterListener(cluster); lifecycleListener = hazelcast.getLifecycleService().addLifecycleListener(clusterListener); membershipListener = cluster.addMembershipListener(clusterListener); break; } catch (Exception e) { if (retry < CLUSTER_STARTUP_RETRY_COUNT) { logger.warn("Failed to start clustering (" + e.getMessage() + "); " + "will retry in " + CLUSTER_STARTUP_RETRY_TIME + " seconds"); try { Thread.sleep(CLUSTER_STARTUP_RETRY_TIME*1000); } catch (InterruptedException ie) { /* ignore */ } } else { logger.error("Unable to start clustering - continuing in local mode", e); state = State.stopped; } } } while (retry++ < CLUSTER_STARTUP_RETRY_COUNT); if (oldLoader != null) { // Restore previous class loader Thread.currentThread().setContextClassLoader(oldLoader); } return cluster != null; }
停止集群的方法
public void stopCluster() { // Stop the cache services. cacheStats = null; // Update the running state of the cluster state = State.stopped; // Stop the cluster Hazelcast.shutdownAll(); cluster = null; if (clusterListener != null) { // Wait until the server has updated its internal state while (!clusterListener.isDone()) { try { Thread.sleep(100); } catch (InterruptedException e) { // Ignore } } hazelcast.getLifecycleService().removeLifecycleListener(lifecycleListener); cluster.removeMembershipListener(membershipListener); lifecycleListener = null; membershipListener = null; clusterListener = null; } // Reset the node ID XMPPServer.getInstance().setNodeID(null); // Reset packet router to use to deliver packets to remote cluster nodes XMPPServer.getInstance().getRoutingTable().setRemotePacketRouter(null); // Reset the session locator to use XMPPServer.getInstance().setRemoteSessionLocator(null); // Set the old serialization strategy was using before clustering was loaded ExternalizableUtil.getInstance().setStrategy(serializationStrategy); }
集群的启动、停止两个方法，下面做一个综合分析，主要执行了如下操作：
（1）设置缓存序列化策略，序列化是为了使数据能够在集群之间复制。
设置之前，先对原有的序列化策略做备份
serializationStrategy = ExternalizableUtil.getInstance().getStrategy(); ExternalizableUtil.getInstance().setStrategy(new ClusterExternalizableUtil());
在集群停止的时候，重置为原来的策略
ExternalizableUtil.getInstance().setStrategy(serializationStrategy);
（2）设置远程Session定位器。集群中的每台机器，都只保存了连接到本机的Session实例。当连接到不同机器的两个客户端发生通信时，就需要用定位器从集群中找到对方。
XMPPServer.getInstance().setRemoteSessionLocator(new RemoteSessionLocator());
在集群停止的时候，置空即可
XMPPServer.getInstance().setRemoteSessionLocator(null);
（3）添加远程包路由器到路由表中，主要是用于数据同步。
XMPPServer.getInstance().getRoutingTable().setRemotePacketRouter(new ClusterPacketRouter());
离开集群时，置空
XMPPServer.getInstance().getRoutingTable().setRemotePacketRouter(null);
（4）根据配置文件，加载Hazelcast的实例
Config config = new ClasspathXmlConfig(HAZELCAST_CONFIG_FILE); config.setInstanceName("openfire"); config.setClassLoader(loader); if (JMXManager.isEnabled() && HAZELCAST_JMX_ENABLED) { config.setProperty("hazelcast.jmx", "true"); config.setProperty("hazelcast.jmx.detailed", "true"); } hazelcast = Hazelcast.newHazelcastInstance(config); cluster = hazelcast.getCluster();
（5）设置节点ID号
XMPPServer.getInstance().setNodeID(NodeID.getInstance(getClusterMemberID()));
（6）设置监听，当集群中状态变化、成员变化时，实现回调
clusterListener = new ClusterListener(cluster); lifecycleListener = hazelcast.getLifecycleService().addLifecycleListener(clusterListener); membershipListener = cluster.addMembershipListener(clusterListener);
ClusterListener中实现了MembershipListener，LifecycleListener接口，当收到回调时，会触发集群管理CluterManager更新事件队列events，并进行事件调度、建立集群缓存等工作，以此实现了集群的响应与管理。
对集群响应的流程总体做一个描述
1、初始状态，Openfire系统启动，并加载了集群插件，第一台完成启动的机器，会被Hazelcast标记为master节点，此时的集群环境，与单机没什么差别
2、当Openfire系统陆续完成启动，新的设备陆续加入、移出集群，Hazelcast本身会完成集群内各种数据同步，然后通过ClusterListener会回调到如下两个方法：
public void memberAdded(MembershipEvent event) { ....... ClusterManager.fireJoinedCluster(StringUtils.getBytes(event.getMember().getUuid()), true); ...... }
public void memberRemoved(MembershipEvent event) { ...... ClusterManager.fireLeftCluster(nodeID); ...... }
3、CluterManager中的fireJoinedCluster()与fireLeftCluster()方法会触发事件队列的events的更新
4、CluterManager事件调度线程dispatcher中，在事件队列更新时将执行CacheFactory.joinedCluster()或CacheFactory.leftCluster()方法更新缓存数据，并通知其他相关组件更新数据，如SessionManager、RouteTableIpml等
5、当有新的客户端发出登录请求，在资源绑定时针将该客户端的Session信息放入集群缓存队列中，由Hazelcast完成数据同步。
6、当集群内客户端发生通信时，使用RemoteSessionLocator获得对方的session实例，再由路由表完成消息路由。
在第四章《消息路由》中，在路由表中，如果是远程消息，将调用routeToRemoteDomain()方法实现消息路由。
RouteTableImpl.routeToRemoteDomain()方法：
private boolean routeToRemoteDomain(JID jid, Packet packet, boolean routed) { byte[] nodeID = serversCache.get(jid.getDomain()); if (nodeID != null) { if (server.getNodeID().equals(nodeID)) { // This is a route to a remote server connected from this node try { localRoutingTable.getRoute(jid.getDomain()).process(packet); routed = true; } catch (UnauthorizedException e) { Log.error("Unable to route packet " + packet.toXML(), e); } } else { // This is a route to a remote server connected from other node if (remotePacketRouter != null) { routed = remotePacketRouter.routePacket(nodeID, jid, packet); } } } else { // Return a promise of a remote session. This object will queue packets pending // to be sent to remote servers OutgoingSessionPromise.getInstance().process(packet); routed = true; } return routed; }
在集群启动中，设置了ClusterPacketRouter作为路由器RemotePacketRouter，ClusterPacketRouter类：
public class ClusterPacketRouter implements RemotePacketRouter { private static Logger logger = LoggerFactory.getLogger(ClusterPacketRouter.class); public boolean routePacket(byte[] nodeID, JID receipient, Packet packet) { // Send the packet to the specified node and let the remote node deliver the packet to the recipient try { CacheFactory.doClusterTask(new RemotePacketExecution(receipient, packet), nodeID); return true; } catch (IllegalStateException e) { logger.warn("Error while routing packet to remote node: " + e); return false; } } public void broadcastPacket(Message packet) { // Execute the broadcast task across the cluster CacheFactory.doClusterTask(new BroadcastMessage(packet)); } }
使用集群中的计算任务，指定一个节点完成消息路由：
CacheFactory.doClusterTask(new RemotePacketExecution(receipient, packet), nodeID);
而RemotePacketExecution实际是一个线程，其run()方法：
public void run() { XMPPServer.getInstance().getRoutingTable().routePacket(recipient, packet, false); }
也就是说，集群中的消息路由，如果通信双方是分处于两台机器上，那么将使用集群将消息指定由对应的主机执行消息路由。
Over!
标签：block 定义 logs oca over data setdaemon com packet
原文地址：http://www.cnblogs.com/Fordestiny/p/7694294.html
