eureka服务端启动流程

文章目录

初始化

现在开始看eureka服务端是怎么启动的。首先从主类上标记的注解@EnableEurekaServer开始分析，其实没啥，就是@Import导入了EurekaServerMarkerConfiguration组件

@Target(ElementType.TYPE)@Retention(RetentionPolicy.RUNTIME)@Documented@Import(EurekaServerMarkerConfiguration.class)public @interfaceEnableEurekaServer{}

EurekaServerMarkerConfiguration组件创建了一个Marker对象，顾名思义就是用来标记的，其实就用标记当前应用为eureka服务端应用。

@ConfigurationpublicclassEurekaServerMarkerConfiguration{@Beanpublic Marker eurekaServerMarkerBean(){returnnewMarker();}classMarker{}}

不要忘了，springboot可以通过spi机制进行定制，所以看下spring.factories文件，这里我们看到定义了自动配置类EurekaServerAutoConfiguration，接下来分析这个类即可。

org.springframework.boot.autoconfigure.EnableAutoConfiguration=\
  org.springframework.cloud.netflix.eureka.server.EurekaServerAutoConfiguration

通过类的声明，我们可以看到导入了EurekaServerInitializerConfiguration组件，刚才创建的Marker Bean也派上用场了，这里就是判断当容器中的Marker Bean存在时，才会对EurekaServerAutoConfiguration进行解析。

@Configuration@Import(EurekaServerInitializerConfiguration.class)@ConditionalOnBean(EurekaServerMarkerConfiguration.Marker.class)@EnableConfigurationProperties({ EurekaDashboardProperties.class,
        InstanceRegistryProperties.class})@PropertySource("classpath:/eureka/server.properties")publicclassEurekaServerAutoConfigurationextendsWebMvcConfigurerAdapter{......@Bean@ConditionalOnProperty(prefix ="eureka.dashboard", name ="enabled", matchIfMissing =true)public EurekaController eurekaController(){returnnewEurekaController(this.applicationInfoManager);}@Beanpublic PeerAwareInstanceRegistry peerAwareInstanceRegistry(
            ServerCodecs serverCodecs){this.eurekaClient.getApplications();// force initializationreturnnewInstanceRegistry(this.eurekaServerConfig,this.eurekaClientConfig,
                serverCodecs,this.eurekaClient,this.instanceRegistryProperties.getExpectedNumberOfClientsSendingRenews(),this.instanceRegistryProperties.getDefaultOpenForTrafficCount());}@Bean@ConditionalOnMissingBeanpublic PeerEurekaNodes peerEurekaNodes(PeerAwareInstanceRegistry registry,
            ServerCodecs serverCodecs){returnnewRefreshablePeerEurekaNodes(registry,this.eurekaServerConfig,this.eurekaClientConfig, serverCodecs,this.applicationInfoManager);}@Beanpublic EurekaServerContext eurekaServerContext(ServerCodecs serverCodecs,
            PeerAwareInstanceRegistry registry, PeerEurekaNodes peerEurekaNodes){returnnewDefaultEurekaServerContext(this.eurekaServerConfig, serverCodecs,
                registry, peerEurekaNodes,this.applicationInfoManager);}@Beanpublic EurekaServerBootstrap eurekaServerBootstrap(PeerAwareInstanceRegistry registry,
            EurekaServerContext serverContext){returnnewEurekaServerBootstrap(this.applicationInfoManager,this.eurekaClientConfig,this.eurekaServerConfig, registry,
                serverContext);}......}

看下这个配置类创建了哪些Bean吧，EurekaController是用来处理仪表盘的，PeerEurekaNodes和PeerAwareInstanceRegistry这是两个集群相关的Bean，EurekaServerBootstrap待会分析，在初始化上下文的时候会用到，现在分析EurekaServerContext，由于initialize()方法存在@PostConstruct注解，因此在实例化以后会被调用。

@PostConstruct@Overridepublicvoidinitialize(){
        logger.info("Initializing ...");
        peerEurekaNodes.start();try{
            registry.init(peerEurekaNodes);}catch(Exception e){thrownewRuntimeException(e);}
        logger.info("Initialized");}

创建集群

这里调用

peerEurekaNodes.start()

开启线程周期性地调用

updatePeerEurekaNodes(resolvePeerUrls());

。在resolvePeerUrls()方法中，首先通过内部属性applicationInfoManager的getInfo()方法获取InstanceInfo实例对象。

protected List<String>resolvePeerUrls(){
        InstanceInfo myInfo = applicationInfoManager.getInfo();// clientConfig(EurekaClientConfigBean)中的属性会跟"eureka.client"开头的配置项绑定// 这里其实是通过EurekaClientConfigBean的region到availabilityZones(HashMap)中获取对应的value，记作zone// zone的默认值是defaultZone
        String zone = InstanceInfo.getZone(clientConfig.getAvailabilityZones(clientConfig.getRegion()), myInfo);// 通过EurekaClientConfigBean的useDnsForFetchingServiceUrls判断副本来源，默认都是从配置中获取// 从属性serviceUrl(HashMap->service-url配置项)中根据zone的值(默认为defaultZone)获取urls// 将这些分区副本的url存到ArrayList<String>中
        List<String> replicaUrls = EndpointUtils
                .getDiscoveryServiceUrls(clientConfig, zone,newEndpointUtils.InstanceInfoBasedUrlRandomizer(myInfo));// 将本节点从现有的分区中移除// 做法isThisMyUrl是从url中获取hostname，再从InstanceInfo中获取本地hostname，把两者进行比较，// 相同返回true，进行removeint idx =0;while(idx < replicaUrls.size()){if(isThisMyUrl(replicaUrls.get(idx))){
                replicaUrls.remove(idx);}else{
                idx++;}}return replicaUrls;}

看下InstanceInfo是怎么被实例化的，springboot的spi定制化太强大了，可以轻而易举地整合其他框架，这里也是通过这个实现的，还是EurekaClientAutoConfiguration，这里通过eurekaApplicationInfoManager()创建InstanceInfo的实例对象，然后注入到ApplicationInfoManager里面去的，再来看InstanceInfo怎么被实例化的。

publicclassEurekaClientAutoConfiguration{@Bean@ConditionalOnMissingBean(value = ApplicationInfoManager.class, search = SearchStrategy.CURRENT)public ApplicationInfoManager eurekaApplicationInfoManager(
            EurekaInstanceConfig config){
        InstanceInfo instanceInfo =newInstanceInfoFactory().create(config);returnnewApplicationInfoManager(config, instanceInfo);}}

注入eurekaApplicationInfoManager()方法的EurekaInstanceConfig默认是EurekaInstanceConfigBean实现的。到这里可以把流程梳理一下。首先创建EurekaInstanceConfigBean实例Bean，而这个实例Bean中的属性跟"eureka.instance"开头的配置项绑定的。接着使用这个配置创建InstanceInfo实例对象，表示当前节点的实例信息，再注入到ApplicationInfoManager中。那我们现在就知道resolvePeerUrls()方法的InstanceInfo怎么来得了。再继续往下面看，接下来就是通过配置项获取集群中所有节点的url，作为updatePeerEurekaNodes()方法参数。接下来总算可以分析updatePeerEurekaNodes()方法，前面经过一系列的Bean注入和配置项获取，总算到updatePeerEurekaNodes()方法调用。

protectedvoidupdatePeerEurekaNodes(List<String> newPeerUrls){if(newPeerUrls.isEmpty()){
            logger.warn("The replica size seems to be empty. Check the route 53 DNS Registry");return;}

        Set<String> toShutdown =newHashSet<>(peerEurekaNodeUrls);
        toShutdown.removeAll(newPeerUrls);
        Set<String> toAdd =newHashSet<>(newPeerUrls);
        toAdd.removeAll(peerEurekaNodeUrls);if(toShutdown.isEmpty()&& toAdd.isEmpty()){// No changereturn;}// Remove peers no long available
        List<PeerEurekaNode> newNodeList =newArrayList<>(peerEurekaNodes);if(!toShutdown.isEmpty()){
            logger.info("Removing no longer available peer nodes {}", toShutdown);int i =0;while(i < newNodeList.size()){
                PeerEurekaNode eurekaNode = newNodeList.get(i);if(toShutdown.contains(eurekaNode.getServiceUrl())){
                    newNodeList.remove(i);
                    eurekaNode.shutDown();}else{
                    i++;}}}// 依次添加集群中其他节点if(!toAdd.isEmpty()){
            logger.info("Adding new peer nodes {}", toAdd);for(String peerUrl : toAdd){
                newNodeList.add(createPeerEurekaNode(peerUrl));}}this.peerEurekaNodes = newNodeList;this.peerEurekaNodeUrls =newHashSet<>(newPeerUrls);}

核心就是createPeerEurekaNode(peerUrl)，根据集群中url创建节点PeerEurekaNode，都看到这里了，死磕到底吧，看下createPeerEurekaNode(peerUrl)方法。

protected PeerEurekaNode createPeerEurekaNode(String peerEurekaNodeUrl){
        HttpReplicationClient replicationClient = JerseyReplicationClient.createReplicationClient(serverConfig, serverCodecs, peerEurekaNodeUrl);
        String targetHost =hostFromUrl(peerEurekaNodeUrl);if(targetHost == null){
            targetHost ="host";}returnnewPeerEurekaNode(registry, targetHost, peerEurekaNodeUrl, replicationClient, serverConfig);}

peerEurekaNodeUrl就是前面获取的集群中其他节点的url，这里先创建一个副本客户端HttpReplicationClient实例对象，再对PeerEurekaNode进行实例化，此时会创建任务，在任务里通过Jersey框架给集群中其他节点发送http请求，总算获取到集群中其他节点信息了。

任务处理模型

实例化之后可以通过

batchingDispatcher.process();

对任务进行处理，本质是将任务添加到队列acceptorQueue(LinkedBlockingQueue)。

voidprocess(ID id, T task,long expiryTime){
        acceptorQueue.add(newTaskHolder<ID, T>(id, task, expiryTime));
        acceptedTasks++;}

然后在AcceptorExecutor的AcceptorRunner线程run()中周期性处理这些任务

publicvoidrun(){long scheduleTime =0;while(!isShutdown.get()){try{// 从队列中取出任务drainInputQueues();int totalItems = processingOrder.size();// 如果没有过期就进行处理long now = System.currentTimeMillis();if(scheduleTime < now){
                        scheduleTime = now + trafficShaper.transmissionDelay();}if(scheduleTime <= now){assignBatchWork();assignSingleItemWork();}// If no worker is requesting data or there is a delay injected by the traffic shaper,// sleep for some time to avoid tight loop.if(totalItems == processingOrder.size()){
                        Thread.sleep(10);}}catch(InterruptedException ex){// Ignore}catch(Throwable e){// Safe-guard, so we never exit this loop in an uncontrolled way.
                    logger.warn("Discovery AcceptorThread error", e);}}}

其实就是从acceptorQueue中poll()出任务，添加到pendingTasks(HashMap)中，key是任务id，value是任务。

privatevoiddrainInputQueues()throws InterruptedException {do{drainReprocessQueue();drainAcceptorQueue();if(!isShutdown.get()){// 队列全空时延时等待任务加入if(reprocessQueue.isEmpty()&& acceptorQueue.isEmpty()&& pendingTasks.isEmpty()){
                        TaskHolder<ID, T> taskHolder = acceptorQueue.poll(10, TimeUnit.MILLISECONDS);if(taskHolder != null){appendTaskHolder(taskHolder);}}}}while(!reprocessQueue.isEmpty()||!acceptorQueue.isEmpty()|| pendingTasks.isEmpty());}privatevoiddrainAcceptorQueue(){while(!acceptorQueue.isEmpty()){appendTaskHolder(acceptorQueue.poll());}}privatevoidappendTaskHolder(TaskHolder<ID, T> taskHolder){if(isFull()){
                pendingTasks.remove(processingOrder.poll());
                queueOverflows++;}
            TaskHolder<ID, T> previousTask = pendingTasks.put(taskHolder.getId(), taskHolder);if(previousTask == null){
                processingOrder.add(taskHolder.getId());}else{
                overriddenTasks++;}}

还是在本线程中收集任务，将刚才加入队列的任务都添加batchWorkQueue中，这些所有要处理的任务都在batchWorkQueue里了。

voidassignBatchWork(){if(hasEnoughTasksForNextBatch()){if(batchWorkRequests.tryAcquire(1)){long now = System.currentTimeMillis();int len = Math.min(maxBatchingSize, processingOrder.size());
                    List<TaskHolder<ID, T>> holders =newArrayList<>(len);while(holders.size()< len &&!processingOrder.isEmpty()){
                        ID id = processingOrder.poll();
                        TaskHolder<ID, T> holder = pendingTasks.remove(id);if(holder.getExpiryTime()> now){
                            holders.add(holder);}else{
                            expiredTasks++;}}if(holders.isEmpty()){
                        batchWorkRequests.release();}else{
                        batchSizeMetric.record(holders.size(), TimeUnit.MILLISECONDS);
                        batchWorkQueue.add(holders);}}}}

接下是就是真正的处理这些任务

processor.process(tasks)

了

publicvoidrun(){try{while(!isShutdown.get()){// 将保存批量任务的holders从队列batchWorkQueue中取出来
                    List<TaskHolder<ID, T>> holders =getWork();
                    metrics.registerExpiryTimes(holders);

                    List<T> tasks =getTasksOf(holders);// 真正的处理在这里
                    ProcessingResult result = processor.process(tasks);switch(result){case Success:break;case Congestion:case TransientError:
                            taskDispatcher.reprocess(holders, result);break;case PermanentError:
                            logger.warn("Discarding {} tasks of {} due to permanent error", holders.size(), workerName);}
                    metrics.registerTaskResult(result, tasks.size());}}catch(InterruptedException e){// Ignore}catch(Throwable e){// Safe-guard, so we never exit this loop in an uncontrolled way.
                logger.warn("Discovery WorkerThread error", e);}}

到这里对eureka任务调度模型总结下：首先batchingDispatcher将要处理的任务添加到acceptorQueue队列，然后线程从acceptorQueue将要处理的任务取出来缓存到pendingTasks，最后如果可以分发任务，就将任务合并到holders(ArrayList)，然后在另外一个线程中批量处理

processor.process(tasks)

，其实这个模型设计得很好的，工作中可以参考下。

现在我们还在EurekaServerContext的initialize()方法，看看注册初始化做的事情

registry.init(peerEurekaNodes);

publicvoidinit(PeerEurekaNodes peerEurekaNodes)throws Exception {// 定时刷新lastBucket值this.numberOfReplicationsLastMin.start();this.peerEurekaNodes = peerEurekaNodes;// 实例化响应缓存initializedResponseCache();// 开启自动续约的任务scheduleRenewalThresholdUpdateTask();initRemoteRegionRegistry();try{
            Monitors.registerObject(this);}catch(Throwable e){
            logger.warn("Cannot register the JMX monitor for the InstanceRegistry :", e);}}

到这里为止EurekaServerContext的实例化彻底完成了，意味着eureka服务上下文创建好了。

再看下服务端启动的最后一步，由于EurekaServerInitializerConfiguration.java实现了SmartLifecycle接口，所在start()会被spring调用，此时EurekaServerBootstrap.java的contextInitialized()会被调用。其实主要就做了两件事，先把集群中其他节点的实例信息同步过来

this.registry.syncUp()

，再更新每分钟续约数，开个自动续约的任务。

服务剔除任务

服务剔除任务是在AbstractInstanceRegistry.java的postInit()方法中开启的，本质是定时执行evict()方法。

publicvoidevict(long additionalLeaseMs){
        logger.debug("Running the evict task");// 自我保护机制，如果开启了自我保护机制，并且每分钟续约数小于期望数numberOfRenewsPerMinThreshold// 就不会剔除服务了if(!isLeaseExpirationEnabled()){
            logger.debug("DS: lease expiration is currently disabled.");return;}// 找到过期的实例
        List<Lease<InstanceInfo>> expiredLeases =newArrayList<>();for(Entry<String, Map<String, Lease<InstanceInfo>>> groupEntry : registry.entrySet()){
            Map<String, Lease<InstanceInfo>> leaseMap = groupEntry.getValue();if(leaseMap != null){for(Entry<String, Lease<InstanceInfo>> leaseEntry : leaseMap.entrySet()){
                    Lease<InstanceInfo> lease = leaseEntry.getValue();if(lease.isExpired(additionalLeaseMs)&& lease.getHolder()!= null){
                        expiredLeases.add(lease);}}}}// To compensate for GC pauses or drifting local time, we need to use current registry size as a base for// triggering self-preservation. Without that we would wipe out full registry.int registrySize =(int)getLocalRegistrySize();int registrySizeThreshold =(int)(registrySize * serverConfig.getRenewalPercentThreshold());int evictionLimit = registrySize - registrySizeThreshold;// 随机清除，如果按顺序清除得话可能会清除掉整个应用int toEvict = Math.min(expiredLeases.size(), evictionLimit);if(toEvict >0){
            logger.info("Evicting {} items (expired={}, evictionLimit={})", toEvict, expiredLeases.size(), evictionLimit);

            Random random =newRandom(System.currentTimeMillis());for(int i =0; i < toEvict; i++){// Pick a random item (Knuth shuffle algorithm)int next = i + random.nextInt(expiredLeases.size()- i);
                Collections.swap(expiredLeases, i, next);
                Lease<InstanceInfo> lease = expiredLeases.get(i);

                String appName = lease.getHolder().getAppName();
                String id = lease.getHolder().getId();
                EXPIRED.increment();
                logger.warn("DS: Registry: expired lease for {}/{}", appName, id);internalCancel(appName, id,false);}}}

这就是eureka的自我保护机制，如果开启了自我保护机制，判断最近一分钟的心跳数是否大于期望收到的心跳数，如果小于期望值得话，说明有服务不在线，可能是重启或者宕机就不会剔除了，等他上线再说。

@OverridepublicbooleanisLeaseExpirationEnabled(){if(!isSelfPreservationModeEnabled()){// The self preservation mode is disabled, hence allowing the instances to expire.returntrue;}return numberOfRenewsPerMinThreshold >0&&getNumOfRenewsInLastMin()> numberOfRenewsPerMinThreshold;}

evictionTimestamp是服务过期得时间戳，如果有值说明服务过期；lastUpdateTimestamp是最近一次得续约时间(心跳包发送得时间)，duration为续约时间间隔，如果

System.currentTimeMillis() > (lastUpdateTimestamp + duration + additionalLeaseMs))

，说明到当前时间为止还没有收到续约心跳，则任务过期。

publicbooleanisExpired(long additionalLeaseMs){return(evictionTimestamp >0|| System.currentTimeMillis()>(lastUpdateTimestamp + duration + additionalLeaseMs));}

剔除服务是在internalCancel()方法中，将要剔除得服务从registry的Map中移除remove(id)掉，然后清除缓存。

protectedbooleaninternalCancel(String appName, String id,boolean isReplication){try{
            read.lock();
            CANCEL.increment(isReplication);
            Map<String, Lease<InstanceInfo>> gMap = registry.get(appName);
            Lease<InstanceInfo> leaseToCancel = null;if(gMap != null){
                leaseToCancel = gMap.remove(id);}synchronized(recentCanceledQueue){
                recentCanceledQueue.add(newPair<Long, String>(System.currentTimeMillis(), appName +"("+ id +")"));}
            InstanceStatus instanceStatus = overriddenInstanceStatusMap.remove(id);if(instanceStatus != null){
                logger.debug("Removed instance id {} from the overridden map which has value {}", id, instanceStatus.name());}if(leaseToCancel == null){
                CANCEL_NOT_FOUND.increment(isReplication);
                logger.warn("DS: Registry: cancel failed because Lease is not registered for: {}/{}", appName, id);returnfalse;}else{
                leaseToCancel.cancel();
                InstanceInfo instanceInfo = leaseToCancel.getHolder();
                String vip = null;
                String svip = null;if(instanceInfo != null){
                    instanceInfo.setActionType(ActionType.DELETED);
                    recentlyChangedQueue.add(newRecentlyChangedItem(leaseToCancel));
                    instanceInfo.setLastUpdatedTimestamp();
                    vip = instanceInfo.getVIPAddress();
                    svip = instanceInfo.getSecureVipAddress();}invalidateCache(appName, vip, svip);
                logger.info("Cancelled instance {}/{} (replication={})", appName, id, isReplication);returntrue;}}finally{
            read.unlock();}}

现在总结下eureka服务端启动的过程：首先从配置文件中获取集群中每个节点的信息，然后创建定时任务周期性发心跳包给其他节点，然后从其他节点将实例信息同步过来。