Spring Cloud Eureka 全解 (4) - 核心流程-服务与实例列表获取详解

原创
2019/08/30 10:15
阅读数 147

本文基于SpringCloud-Dalston.SR5

关于服务与实例列表获取

EurekaClient端

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 List<Server> allServerList = Collections.synchronizedList(new ArrayList<Server>());

public void setServersList(List lsrv) {
    //写入allServerList的代码,这里略
}

@Override
public List<Server> 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<Server> reachableServers = lb.getReachableServers();
        //获取服务实例列表,调用的就是刚刚提到的getAllServers
        List<Server> 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 AtomicReference<Applications> localRegionApps = new AtomicReference<Applications>();

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<Applications> 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<Applications> 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:

  1. 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。
  2. 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。
  3. 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

EurekaServer端

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

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