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本篇内容主要讲解“Spring Cloud Eureka的服务与列表获取的方法是什么”，感兴趣的朋友不妨来看看。本文介绍的方法操作简单快捷，实用性强。下面就让小编来带大家学习“Spring Cloud Eureka的服务与列表获取的方法是什么”吧!
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我们从Ribbon说起：EurekaClient也存在缓存，应用服务实例列表信息在每个EurekaClient服务消费端都有缓存。一般的，Ribbon的LoadBalancer会读取这个缓存，来知道当前有哪些实例可以调用，从而进行负载均衡。这个loadbalancer同样也有缓存。
首先看这个LoadBalancer的缓存更新机制，相关类是PollingServerListUpdater：
final Runnable wrapperRunnable = new Runnable() {
@Override
public void run() {
if (!isActive.get()) {
if (scheduledFuture != null) {
scheduledFuture.cancel(true);
}
return;
}
try {
//从EurekaClient缓存中获取服务实例列表，保存在本地缓存
updateAction.doUpdate();
lastUpdated = System.currentTimeMillis();
} catch (Exception e) {
logger.warn("Failed one update cycle", e);
}
}
};
//定时调度
scheduledFuture = getRefreshExecutor().scheduleWithFixedDelay(
wrapperRunnable,
initialDelayMs,
refreshIntervalMs,
TimeUnit.MILLISECONDS
);这个updateAction.doUpdate();就是从EurekaClient缓存中获取服务实例列表，保存在BaseLoadBalancer的本地缓存：
protected volatile ListallServerList = Collections.synchronizedList(new ArrayList ()); public void setServersList(List lsrv) { //写入allServerList的代码，这里略 } @Override public List getAllServers() { return Collections.unmodifiableList(allServerList); }
这里的getAllServers会在每个负载均衡规则中被调用，例如RoundRobinRule：
public Server choose(ILoadBalancer lb, Object key) {
if (lb == null) {
log.warn("no load balancer");
return null;
}
Server server = null;
int count = 0;
while (server == null && count++ < 10) {
List reachableServers = lb.getReachableServers();
//获取服务实例列表，调用的就是刚刚提到的getAllServers
List allServers = lb.getAllServers();
int upCount = reachableServers.size();
int serverCount = allServers.size();
if ((upCount == 0) || (serverCount == 0)) {
log.warn("No up servers available from load balancer: " + lb);
return null;
}
int nextServerIndex = incrementAndGetModulo(serverCount);
server = allServers.get(nextServerIndex);
if (server == null) {
/* Transient. */
Thread.yield();
continue;
}
if (server.isAlive() && (server.isReadyToServe())) {
return (server);
}
// Next.
server = null;
}
if (count >= 10) {
log.warn("No available alive servers after 10 tries from load balancer: "
+ lb);
}
return server;
} 这个缓存需要注意下，有时候我们只修改了EurekaClient缓存的更新时间，但是没有修改这个LoadBalancer的刷新本地缓存时间，就是ribbon.ServerListRefreshInterval,这个参数可以设置的很小，因为没有从网络读取，就是从一个本地缓存刷到另一个本地缓存（如何配置缓存配置来实现服务实例快速下线快速感知快速刷新，可以参考我的另一篇文章）。
然后我们来看一下EurekaClient本身的缓存，直接看关键类DiscoveryClient的相关源码，我们这里只关心本地Region的，多Region配置我们先忽略：
//本地缓存，可以理解为是一个软链接 private final AtomicReferencelocalRegionApps = new AtomicReference (); private void initScheduledTasks() { //如果配置为需要拉取服务列表，则设置定时拉取任务，这个配置默认是需要拉取服务列表 if (clientConfig.shouldFetchRegistry()) { // registry cache refresh timer int registryFetchIntervalSeconds = clientConfig.getRegistryFetchIntervalSeconds(); int expBackOffBound = clientConfig.getCacheRefreshExecutorExponentialBackOffBound(); scheduler.schedule( new TimedSupervisorTask( "cacheRefresh", scheduler, cacheRefreshExecutor, registryFetchIntervalSeconds, TimeUnit.SECONDS, expBackOffBound, new CacheRefreshThread() ), registryFetchIntervalSeconds, TimeUnit.SECONDS); } //其他定时任务初始化的代码，忽略 } //定时从EurekaServer拉取服务列表的任务 class CacheRefreshThread implements Runnable { public void run() { refreshRegistry(); } } void refreshRegistry() { try { //多Region配置处理代码，忽略 boolean success = fetchRegistry(remoteRegionsModified); if (success) { registrySize = localRegionApps.get().size(); lastSuccessfulRegistryFetchTimestamp = System.currentTimeMillis(); } //日志代码，忽略 } catch (Throwable e) { logger.error("Cannot fetch registry from server", e); } } //定时从EurekaServer拉取服务列表的核心方法 private boolean fetchRegistry(boolean forceFullRegistryFetch) { Stopwatch tracer = FETCH_REGISTRY_TIMER.start(); try { Applications applications = getApplications(); //判断，如果是第一次拉取，或者app列表为空，就进行全量拉取，否则就会进行增量拉取 if (clientConfig.shouldDisableDelta() || (!Strings.isNullOrEmpty(clientConfig.getRegistryRefreshSingleVipAddress())) || forceFullRegistryFetch || (applications == null) || (applications.getRegisteredApplications().size() == 0) || (applications.getVersion() == -1)) //Client application does not have latest library supporting delta { getAndStoreFullRegistry(); } else { getAndUpdateDelta(applications); } applications.setAppsHashCode(applications.getReconcileHashCode()); logTotalInstances(); } catch (Throwable e) { logger.error(PREFIX + appPathIdentifier + " - was unable to refresh its cache! status = " + e.getMessage(), e); return false; } finally { if (tracer != null) { tracer.stop(); } } //缓存更新完成，发送个event给观察者，目前没啥用 onCacheRefreshed(); // 检查下远端的服务实例列表里面包括自己，并且状态是否对，这里我们不关心 updateInstanceRemoteStatus(); // registry was fetched successfully, so return true return true; } //全量拉取代码 private void getAndStoreFullRegistry() throws Throwable { long currentUpdateGeneration = fetchRegistryGeneration.get(); Applications apps = null; //访问/eureka/apps接口，拉取所有服务实例信息 EurekaHttpResponse httpResponse = clientConfig.getRegistryRefreshSingleVipAddress() == null ? eurekaTransport.queryClient.getApplications(remoteRegionsRef.get()) : eurekaTransport.queryClient.getVip(clientConfig.getRegistryRefreshSingleVipAddress(), remoteRegionsRef.get()); if (httpResponse.getStatusCode() == Status.OK.getStatusCode()) { apps = httpResponse.getEntity(); } logger.info("The response status is {}", httpResponse.getStatusCode()); if (apps == null) { logger.error("The application is null for some reason. Not storing this information"); } else if (fetchRegistryGeneration.compareAndSet(currentUpdateGeneration, currentUpdateGeneration + 1)) { localRegionApps.set(this.filterAndShuffle(apps)); logger.debug("Got full registry with apps hashcode {}", apps.getAppsHashCode()); } else { logger.warn("Not updating applications as another thread is updating it already"); } } //增量拉取代码 private void getAndUpdateDelta(Applications applications) throws Throwable { long currentUpdateGeneration = fetchRegistryGeneration.get(); Applications delta = null; //访问/eureka/delta接口，拉取所有服务实例增量信息 EurekaHttpResponse httpResponse = eurekaTransport.queryClient.getDelta(remoteRegionsRef.get()); if (httpResponse.getStatusCode() == Status.OK.getStatusCode()) { delta = httpResponse.getEntity(); } if (delta == null) { //如果delta为空，拉取增量失败，就全量拉取 logger.warn("The server does not allow the delta revision to be applied because it is not safe. " + "Hence got the full registry."); getAndStoreFullRegistry(); } else if (fetchRegistryGeneration.compareAndSet(currentUpdateGeneration, currentUpdateGeneration + 1)) { //这里设置原子锁的原因是怕某次调度网络请求时间过长，导致同一时间有多线程拉取到增量信息并发修改 //拉取增量成功，检查hashcode是否一样，不一样的话也会全量拉取 logger.debug("Got delta update with apps hashcode {}", delta.getAppsHashCode()); String reconcileHashCode = ""; if (fetchRegistryUpdateLock.tryLock()) { try { updateDelta(delta); reconcileHashCode = getReconcileHashCode(applications); } finally { fetchRegistryUpdateLock.unlock(); } } else { logger.warn("Cannot acquire update lock, aborting getAndUpdateDelta"); } // There is a diff in number of instances for some reason if (!reconcileHashCode.equals(delta.getAppsHashCode()) || clientConfig.shouldLogDeltaDiff()) { reconcileAndLogDifference(delta, reconcileHashCode); // this makes a remoteCall } } else { logger.warn("Not updating application delta as another thread is updating it already"); logger.debug("Ignoring delta update with apps hashcode {}, as another thread is updating it already", delta.getAppsHashCode()); } }
以上就是对于EurekaClient拉取服务实例信息的源代码分析，总结EurekaClient 重要缓存如下：
EurekaClient第一次全量拉取，定时增量拉取应用服务实例信息，保存在缓存中。
EurekaClient增量拉取失败，或者增量拉取之后对比hashcode发现不一致，就会执行全量拉取，这样避免了网络某时段分片带来的问题。
同时对于服务调用，如果涉及到ribbon负载均衡，那么ribbon对于这个实例列表也有自己的缓存，这个缓存定时从EurekaClient的缓存更新
在EurekaServer端，所有的读取请求都是读的ReadOnlyMap（这个可以配置） 有定时任务会定时从ReadWriteMap同步到ReadOnlyMap这个时间配置是：
#eureka server刷新readCacheMap的时间，注意，client读取的是readCacheMap，这个时间决定了多久会把readWriteCacheMap的缓存更新到readCacheMap上 #默认30s eureka.server.responseCacheUpdateInvervalMs=3000
相关代码：
if (shouldUseReadOnlyResponseCache) {
timer.schedule(getCacheUpdateTask(),
new Date(((System.currentTimeMillis() / responseCacheUpdateIntervalMs) * responseCacheUpdateIntervalMs)
+ responseCacheUpdateIntervalMs),
responseCacheUpdateIntervalMs);
}
private TimerTask getCacheUpdateTask() {
return new TimerTask() {
@Override
public void run() {
logger.debug("Updating the client cache from response cache");
for (Key key : readOnlyCacheMap.keySet()) {
if (logger.isDebugEnabled()) {
Object[] args = {key.getEntityType(), key.getName(), key.getVersion(), key.getType()};
logger.debug("Updating the client cache from response cache for key : {} {} {} {}", args);
}
try {
CurrentRequestVersion.set(key.getVersion());
Value cacheValue = readWriteCacheMap.get(key);
Value currentCacheValue = readOnlyCacheMap.get(key);
if (cacheValue != currentCacheValue) {
readOnlyCacheMap.put(key, cacheValue);
}
} catch (Throwable th) {
logger.error("Error while updating the client cache from response cache", th);
}
}
}
};
}ReadWriteMap是一个LoadingCache，将Registry中的服务实例信息封装成要返回的http响应（分别是经过gzip压缩和非压缩的），同时还有两个特殊key，ALL_APPS和ALL_APPS_DELTA ALL_APPS就是所有服务实例信息 ALL_APPS_DELTA就是之前讲注册说的RecentlyChangedQueue里面的实例列表封装的http响应信息
到此，相信大家对“Spring Cloud Eureka的服务与列表获取的方法是什么”有了更深的了解，不妨来实际操作一番吧！这里是创新互联网站，更多相关内容可以进入相关频道进行查询，关注我们，继续学习！
