Dubbo（五）：集群容错的实现
前两篇中，我们看到了dubbo在负载均衡和服务路由方面的实现，它为集群功能提供了必要的功能。
今天我们再来看另一个集群组件的实现：集群容错。
1. dubbo 集群容错简介
为了避免单点故障，现在的应用通常至少会部署在两台服务器上。对于一些负载比较高的服务，会部署更多的服务器。对于服务消费者来说，同一环境下出现了多个服务提供者。这时会出现一个问题，服务消费者需要决定选择哪个服务提供者进行调用。另外服务调用失败时的处理措施也是需要考虑的，是重试呢，还是抛出异常，亦或是只打印异常等。为了处理这些问题，Dubbo 定义了集群接口 Cluster 以及 Cluster Invoker。集群 Cluster 用途是将多个服务提供者合并为一个 Cluster Invoker，并将这个 Invoker 暴露给服务消费者。这样一来，服务消费者只需通过这个 Invoker 进行远程调用即可，至于具体调用哪个服务提供者，以及调用失败后如何处理等问题，现在都交给集群模块去处理。集群模块是服务提供者和服务消费者的中间层，为服务消费者屏蔽了服务提供者的情况，这样服务消费者就可以专心处理远程调用相关事宜。
dubbo的集群容错功能由多个组件共同完成：包括 Cluster、Cluster Invoker、Directory、Router 和 LoadBalance 等。它们之间的依赖关系如下：
负载均衡、路由服务是在一次调用中进行的，而容错则是当调用发生异常之后，进行处理策略。
dubbo中主要提供了以下几种容错策略实现：
Failover Cluster - 失败自动切换
Failfast Cluster - 快速失败
Failsafe Cluster - 失败安全
Failback Cluster - 失败自动恢复
Forking Cluster - 并行调用多个服务提供者
2. 集群容错的框架实现
集群接口 Cluster 和 Cluster Invoker，这两者是不同的。Cluster 是接口，而 Cluster Invoker 是一种 Invoker。服务提供者的选择逻辑，以及远程调用失败后的的处理逻辑均是封装在 Cluster Invoker 中。
Cluster 的实现类图如下：
各个Cluster的实现都很简单，也都统一继承了 AbstractCluster, 而该 AbstractCluster 则做了一层统一的拦截器的功能接入，实现如下：
public abstract class AbstractCluster implements Cluster {
private <T> Invoker<T> buildClusterInterceptors(AbstractClusterInvoker<T> clusterInvoker, String key) {
AbstractClusterInvoker<T> last = clusterInvoker;
List<ClusterInterceptor> interceptors = ExtensionLoader.getExtensionLoader(ClusterInterceptor.class).getActivateExtension(clusterInvoker.getUrl(), key);
// 根据需要包装ClusterInvoker, 使用切面的方式进行拦截器接入
// 按先后依次强入拦截器
if (!interceptors.isEmpty()) {
for (int i = interceptors.size() - 1; i >= 0; i--) {
final ClusterInterceptor interceptor = interceptors.get(i);
final AbstractClusterInvoker<T> next = last;
// 使用内部类进行包装拦截器
// 先后顺序如: beforeC -> beforeB -> beforeA (spring中还有Around) -> afterA -> afterB -> afterC (spring中还有afterReturn)
last = new InterceptorInvokerNode<>(clusterInvoker, interceptor, next);
}
}
return last;
}
@Override
public <T> Invoker<T> join(Directory<T> directory) throws RpcException {
// ClusterInvoker 调用入口, 让具体策略实现 doJoin(), 并在其基础上进行包装拦截器, 依据来源 reference.interceptor=xxx
return buildClusterInterceptors(doJoin(directory), directory.getUrl().getParameter(REFERENCE_INTERCEPTOR_KEY));
}
//
protected abstract <T> AbstractClusterInvoker<T> doJoin(Directory<T> directory) throws RpcException;
protected class InterceptorInvokerNode<T> extends AbstractClusterInvoker<T> {
private AbstractClusterInvoker<T> clusterInvoker;
private ClusterInterceptor interceptor;
private AbstractClusterInvoker<T> next;
public InterceptorInvokerNode(AbstractClusterInvoker<T> clusterInvoker,
ClusterInterceptor interceptor,
AbstractClusterInvoker<T> next) {
this.clusterInvoker = clusterInvoker;
this.interceptor = interceptor;
this.next = next;
}
@Override
public Class<T> getInterface() {
return clusterInvoker.getInterface();
}
@Override
public URL getUrl() {
return clusterInvoker.getUrl();
}
@Override
public boolean isAvailable() {
return clusterInvoker.isAvailable();
}
@Override
public Result invoke(Invocation invocation) throws RpcException {
Result asyncResult;
try {
// 拦截器的具体处理逻辑
// 有个 intercept() 的默认方法，其为调用 clusterInvoker.invoke(invocation); 从而实现链式调用
interceptor.before(next, invocation);
asyncResult = interceptor.intercept(next, invocation);
} catch (Exception e) {
// onError callback
if (interceptor instanceof ClusterInterceptor.Listener) {
ClusterInterceptor.Listener listener = (ClusterInterceptor.Listener) interceptor;
listener.onError(e, clusterInvoker, invocation);
}
throw e;
} finally {
interceptor.after(next, invocation);
}
return asyncResult.whenCompleteWithContext((r, t) -> {
// onResponse callback
if (interceptor instanceof ClusterInterceptor.Listener) {
ClusterInterceptor.Listener listener = (ClusterInterceptor.Listener) interceptor;
if (t == null) {
listener.onMessage(r, clusterInvoker, invocation);
} else {
listener.onError(t, clusterInvoker, invocation);
}
}
});
}
@Override
public void destroy() {
clusterInvoker.destroy();
}
@Override
public String toString() {
return clusterInvoker.toString();
}
@Override
protected Result doInvoke(Invocation invocation, List<Invoker<T>> invokers, LoadBalance loadbalance) throws RpcException {
// The only purpose is to build a interceptor chain, so the cluster related logic doesn't matter.
return null;
}
}
}
接下来，我们详细看看，每个集群容错策略都是如何创建的。
// failover 失败自动切换
public class FailoverCluster extends AbstractCluster {
public final static String NAME = "failover";
@Override
public <T> AbstractClusterInvoker<T> doJoin(Directory<T> directory) throws RpcException {
return new FailoverClusterInvoker<>(directory);
}
}
// failfast 快速失败
public class FailfastCluster extends AbstractCluster {
public final static String NAME = "failfast";
@Override
public <T> AbstractClusterInvoker<T> doJoin(Directory<T> directory) throws RpcException {
return new FailfastClusterInvoker<>(directory);
}
}
// failsafe 失败安全
public class FailsafeCluster extends AbstractCluster {
public final static String NAME = "failsafe";
@Override
public <T> AbstractClusterInvoker<T> doJoin(Directory<T> directory) throws RpcException {
return new FailsafeClusterInvoker<>(directory);
}
}
// failback 失败自动恢复
public class FailbackCluster extends AbstractCluster {
public final static String NAME = "failback";
@Override
public <T> AbstractClusterInvoker<T> doJoin(Directory<T> directory) throws RpcException {
return new FailbackClusterInvoker<>(directory);
}
}
// forking 并行调用多个服务提供者
public class ForkingCluster extends AbstractCluster {
public final static String NAME = "forking";
@Override
public <T> AbstractClusterInvoker<T> doJoin(Directory<T> directory) throws RpcException {
return new ForkingClusterInvoker<>(directory);
}
}
// mergeable 合并结果容错
public class MergeableCluster extends AbstractCluster {
public static final String NAME = "mergeable";
@Override
public <T> AbstractClusterInvoker<T> doJoin(Directory<T> directory) throws RpcException {
return new MergeableClusterInvoker<T>(directory);
}
}
3. 具体集群容错的实现
failover, 失败自动切换。这是dubbo的默认集群容错策略，因为它是一个比较通用的策略，即只需做重试即可，保证高可用。
整个集群容错策略的调用入口在 AbstractClusterInvoker.invoke() 中，经过一些通用过程调用后，再由具体策略实现 doInvoke();
// org.apache.dubbo.rpc.cluster.support.AbstractClusterInvoker#invoke
@Override
public Result invoke(final Invocation invocation) throws RpcException {
// 有效性检查
checkWhetherDestroyed();
// binding attachments into invocation.
Map<String, Object> contextAttachments = RpcContext.getContext().getObjectAttachments();
if (contextAttachments != null && contextAttachments.size() != 0) {
((RpcInvocation) invocation).addObjectAttachments(contextAttachments);
}
// 路由服务提供所有的 invokers
List<Invoker<T>> invokers = list(invocation);
// 获取负载均衡器
LoadBalance loadbalance = initLoadBalance(invokers, invocation);
RpcUtils.attachInvocationIdIfAsync(getUrl(), invocation);
// 各子类实现 具体的容错逻辑
return doInvoke(invocation, invokers, loadbalance);
}
3.1. failover 失败自动切换实现
// org.apache.dubbo.rpc.cluster.support.FailoverClusterInvoker#doInvoke
@Override
@SuppressWarnings({"unchecked", "rawtypes"})
public Result doInvoke(Invocation invocation, final List<Invoker<T>> invokers, LoadBalance loadbalance) throws RpcException {
List<Invoker<T>> copyInvokers = invokers;
checkInvokers(copyInvokers, invocation);
String methodName = RpcUtils.getMethodName(invocation);
int len = getUrl().getMethodParameter(methodName, RETRIES_KEY, DEFAULT_RETRIES) + 1;
if (len <= 0) {
len = 1;
}
// retry loop.
RpcException le = null; // last exception.
List<Invoker<T>> invoked = new ArrayList<Invoker<T>>(copyInvokers.size()); // invoked invokers.
Set<String> providers = new HashSet<String>(len);
// 失败自动切换，就是一个重试的过程
for (int i = 0; i < len; i++) {
//Reselect before retry to avoid a change of candidate `invokers`.
//NOTE: if `invokers` changed, then `invoked` also lose accuracy.
if (i > 0) {
// 进行重试时，需要刷新invokers
checkWhetherDestroyed();
copyInvokers = list(invocation);
// check again
checkInvokers(copyInvokers, invocation);
}
// 使用负载均衡选取一个 invoker
Invoker<T> invoker = select(loadbalance, invocation, copyInvokers, invoked);
// 将选中的invoker添加到 invoked 中，避免反复选择一个失效的invoker
invoked.add(invoker);
RpcContext.getContext().setInvokers((List) invoked);
try {
// 调用选中的invoker 远程服务，成功直接返回了，失败则容错能力上
Result result = invoker.invoke(invocation);
if (le != null && logger.isWarnEnabled()) {
logger.warn("Although retry the method " + methodName
+ " in the service " + getInterface().getName()
+ " was successful by the provider " + invoker.getUrl().getAddress()
+ ", but there have been failed providers " + providers
+ " (" + providers.size() + "/" + copyInvokers.size()
+ ") from the registry " + directory.getUrl().getAddress()
+ " on the consumer " + NetUtils.getLocalHost()
+ " using the dubbo version " + Version.getVersion() + ". Last error is: "
+ le.getMessage(), le);
}
// 调用成功直接返回
return result;
} catch (RpcException e) {
// 业务异常则直接抛出，不再重试
if (e.isBiz()) { // biz exception.
throw e;
}
le = e;
} catch (Throwable e) {
le = new RpcException(e.getMessage(), e);
} finally {
providers.add(invoker.getUrl().getAddress());
}
}
throw new RpcException(le.getCode(), "Failed to invoke the method "
+ methodName + " in the service " + getInterface().getName()
+ ". Tried " + len + " times of the providers " + providers
+ " (" + providers.size() + "/" + copyInvokers.size()
+ ") from the registry " + directory.getUrl().getAddress()
+ " on the consumer " + NetUtils.getLocalHost() + " using the dubbo version "
+ Version.getVersion() + ". Last error is: "
+ le.getMessage(), le.getCause() != null ? le.getCause() : le);
}
总结：failover 容错，即是自动重试各可用提供者的过程。
3.2. failback 失败自动恢复的实现
public FailbackClusterInvoker(Directory<T> directory) {
super(directory);
// retries=3
int retriesConfig = getUrl().getParameter(RETRIES_KEY, DEFAULT_FAILBACK_TIMES);
if (retriesConfig <= 0) {
retriesConfig = DEFAULT_FAILBACK_TIMES;
}
// failbacktasks=100
int failbackTasksConfig = getUrl().getParameter(FAIL_BACK_TASKS_KEY, DEFAULT_FAILBACK_TASKS);
if (failbackTasksConfig <= 0) {
failbackTasksConfig = DEFAULT_FAILBACK_TASKS;
}
retries = retriesConfig;
failbackTasks = failbackTasksConfig;
}
// 当调用失败后，将其添加到定时队列中，稍后进行重新请求
private void addFailed(LoadBalance loadbalance, Invocation invocation, List<Invoker<T>> invokers, Invoker<T> lastInvoker) {
if (failTimer == null) {
synchronized (this) {
if (failTimer == null) {
// 以1秒为间隔使用 hash环，扫描任务
failTimer = new HashedWheelTimer(
new NamedThreadFactory("failback-cluster-timer", true),
1,
TimeUnit.SECONDS, 32, failbackTasks);
}
}
}
// 使用 RetryTimerTask 来构建调度的任务
RetryTimerTask retryTimerTask = new RetryTimerTask(loadbalance, invocation, invokers, lastInvoker, retries, RETRY_FAILED_PERIOD);
try {
failTimer.newTimeout(retryTimerTask, RETRY_FAILED_PERIOD, TimeUnit.SECONDS);
} catch (Throwable e) {
logger.error("Failback background works error,invocation->" + invocation + ", exception: " + e.getMessage());
}
}
@Override
protected Result doInvoke(Invocation invocation, List<Invoker<T>> invokers, LoadBalance loadbalance) throws RpcException {
Invoker<T> invoker = null;
try {
checkInvokers(invokers, invocation);
invoker = select(loadbalance, invocation, invokers, null);
// 只调用一次，失败即失败
return invoker.invoke(invocation);
} catch (Throwable e) {
logger.error("Failback to invoke method " + invocation.getMethodName() + ", wait for retry in background. Ignored exception: "
+ e.getMessage() + ", ", e);
// 添加到失败队列中，稍后进行调度
addFailed(loadbalance, invocation, invokers, invoker);
return AsyncRpcResult.newDefaultAsyncResult(null, null, invocation); // ignore
}
}
总结：failback 容错，即是只做一次调用，失败后会开启后续定时任务进行重新调用的过程。
3.3. failfast 快速失败的实现
// org.apache.dubbo.rpc.cluster.support.FailfastClusterInvoker#doInvoke
@Override
public Result doInvoke(Invocation invocation, List<Invoker<T>> invokers, LoadBalance loadbalance) throws RpcException {
checkInvokers(invokers, invocation);
// 使用负载均衡选取一个 可用的 invoker, 然后进行调用即可
// selected = null, 即只一次选择即可完成select
Invoker<T> invoker = select(loadbalance, invocation, invokers, null);
try {
return invoker.invoke(invocation);
} catch (Throwable e) {
if (e instanceof RpcException && ((RpcException) e).isBiz()) { // biz exception.
throw (RpcException) e;
}
throw new RpcException(e instanceof RpcException ? ((RpcException) e).getCode() : 0,
"Failfast invoke providers " + invoker.getUrl() + " " + loadbalance.getClass().getSimpleName()
+ " select from all providers " + invokers + " for service " + getInterface().getName()
+ " method " + invocation.getMethodName() + " on consumer " + NetUtils.getLocalHost()
+ " use dubbo version " + Version.getVersion()
+ ", but no luck to perform the invocation. Last error is: " + e.getMessage(),
e.getCause() != null ? e.getCause() : e);
}
}
// org.apache.dubbo.rpc.cluster.support.AbstractClusterInvoker#select
/**
* Select a invoker using loadbalance policy.</br>
* a) Firstly, select an invoker using loadbalance. If this invoker is in previously selected list, or,
* if this invoker is unavailable, then continue step b (reselect), otherwise return the first selected invoker</br>
* <p>
* b) Reselection, the validation rule for reselection: selected > available. This rule guarantees that
* the selected invoker has the minimum chance to be one in the previously selected list, and also
* guarantees this invoker is available.
*
* @param loadbalance load balance policy
* @param invocation invocation
* @param invokers invoker candidates
* @param selected exclude selected invokers or not
* @return the invoker which will final to do invoke.
* @throws RpcException exception
*/
protected Invoker<T> select(LoadBalance loadbalance, Invocation invocation,
List<Invoker<T>> invokers, List<Invoker<T>> selected) throws RpcException {
if (CollectionUtils.isEmpty(invokers)) {
return null;
}
String methodName = invocation == null ? StringUtils.EMPTY_STRING : invocation.getMethodName();
boolean sticky = invokers.get(0).getUrl()
.getMethodParameter(methodName, CLUSTER_STICKY_KEY, DEFAULT_CLUSTER_STICKY);
//ignore overloaded method
if (stickyInvoker != null && !invokers.contains(stickyInvoker)) {
stickyInvoker = null;
}
//ignore concurrency problem
if (sticky && stickyInvoker != null && (selected == null || !selected.contains(stickyInvoker))) {
if (availablecheck && stickyInvoker.isAvailable()) {
return stickyInvoker;
}
}
Invoker<T> invoker = doSelect(loadbalance, invocation, invokers, selected);
if (sticky) {
stickyInvoker = invoker;
}
return invoker;
}
private Invoker<T> doSelect(LoadBalance loadbalance, Invocation invocation,
List<Invoker<T>> invokers, List<Invoker<T>> selected) throws RpcException {
if (CollectionUtils.isEmpty(invokers)) {
return null;
}
if (invokers.size() == 1) {
return invokers.get(0);
}
Invoker<T> invoker = loadbalance.select(invokers, getUrl(), invocation);
//If the `invoker` is in the `selected` or invoker is unavailable && availablecheck is true, reselect.
if ((selected != null && selected.contains(invoker))
|| (!invoker.isAvailable() && getUrl() != null && availablecheck)) {
try {
Invoker<T> rInvoker = reselect(loadbalance, invocation, invokers, selected, availablecheck);
if (rInvoker != null) {
invoker = rInvoker;
} else {
//Check the index of current selected invoker, if it's not the last one, choose the one at index+1.
int index = invokers.indexOf(invoker);
try {
//Avoid collision
invoker = invokers.get((index + 1) % invokers.size());
} catch (Exception e) {
logger.warn(e.getMessage() + " may because invokers list dynamic change, ignore.", e);
}
}
} catch (Throwable t) {
logger.error("cluster reselect fail reason is :" + t.getMessage() + " if can not solve, you can set cluster.availablecheck=false in url", t);
}
}
return invoker;
}
总结: failfast 容错，使用负载均衡策略选择一次可用的invoker, 进行调用, 异常则抛出，正常则返回结果。
3.4. failsafe 安全失败容错的实现
@Override
public Result doInvoke(Invocation invocation, List<Invoker<T>> invokers, LoadBalance loadbalance) throws RpcException {
try {
checkInvokers(invokers, invocation);
// 与failfast 一样，只使用一次负载均衡策略，选择一个invoker调用即可
// 差别在于返回值，failsafe 不抛出异常，当发生异常时返回一个默认值
Invoker<T> invoker = select(loadbalance, invocation, invokers, null);
return invoker.invoke(invocation);
} catch (Throwable e) {
logger.error("Failsafe ignore exception: " + e.getMessage(), e);
// 将异常信息忽略，返回默认值
return AsyncRpcResult.newDefaultAsyncResult(null, null, invocation); // ignore
}
}
总结: failsafe 容错，即忽略掉所有异常，只返回正式结果。当发生异常时，返回 AsyncRpcResult.newDefaultAsyncResult 作为结果，好像没有发生异常一样。
3.5. forking 并发请求容错实现
// org.apache.dubbo.rpc.cluster.support.ForkingClusterInvoker#doInvoke
@Override
@SuppressWarnings({"unchecked", "rawtypes"})
public Result doInvoke(final Invocation invocation, List<Invoker<T>> invokers, LoadBalance loadbalance) throws RpcException {
try {
checkInvokers(invokers, invocation);
final List<Invoker<T>> selected;
// forks=2
final int forks = getUrl().getParameter(FORKS_KEY, DEFAULT_FORKS);
// timeout=1000
final int timeout = getUrl().getParameter(TIMEOUT_KEY, DEFAULT_TIMEOUT);
if (forks <= 0 || forks >= invokers.size()) {
selected = invokers;
} else {
selected = new ArrayList<>(forks);
while (selected.size() < forks) {
Invoker<T> invoker = select(loadbalance, invocation, invokers, selected);
if (!selected.contains(invoker)) {
//Avoid add the same invoker several times.
selected.add(invoker);
}
}
}
RpcContext.getContext().setInvokers((List) selected);
final AtomicInteger count = new AtomicInteger();
final BlockingQueue<Object> ref = new LinkedBlockingQueue<>();
for (final Invoker<T> invoker : selected) {
// 使用线程池进行并发调用 invoker
// 线程池为无界队列式: executor = Executors.newCachedThreadPool(new NamedInternalThreadFactory("forking-cluster-timer", true));
executor.execute(() -> {
try {
Result result = invoker.invoke(invocation);
// 只要结果响应，则入队到 ref 中
ref.offer(result);
} catch (Throwable e) {
int value = count.incrementAndGet();
if (value >= selected.size()) {
// 当超过forks 数量的异常发生后，将异常信息写入ref中，即外部可以获取结果了
ref.offer(e);
}
}
});
}
try {
// 阻塞获取结果，最长等待 timeout
// 获取第一个结果作为响应依据
Object ret = ref.poll(timeout, TimeUnit.MILLISECONDS);
// 因可以全部异常，获取到的结果可能是个 Throwable 信息，须先判定
if (ret instanceof Throwable) {
Throwable e = (Throwable) ret;
throw new RpcException(e instanceof RpcException ? ((RpcException) e).getCode() : 0, "Failed to forking invoke provider " + selected + ", but no luck to perform the invocation. Last error is: " + e.getMessage(), e.getCause() != null ? e.getCause() : e);
}
return (Result) ret;
} catch (InterruptedException e) {
throw new RpcException("Failed to forking invoke provider " + selected + ", but no luck to perform the invocation. Last error is: " + e.getMessage(), e);
}
} finally {
// clear attachments which is binding to current thread.
RpcContext.getContext().clearAttachments();
}
}
总结: forking 容错，即是同时发起n个并发请求调用提供者，谁最先响应则返回谁的结果。其他结果则全部忽略。可以说是非常耗资源的一种方式了，不过总是有相应的应用场景，所以存在。
3.6. broadcast 广播容错的实现
// org.apache.dubbo.rpc.cluster.support.BroadcastClusterInvoker#doInvoke
@Override
@SuppressWarnings({"unchecked", "rawtypes"})
public Result doInvoke(final Invocation invocation, List<Invoker<T>> invokers, LoadBalance loadbalance) throws RpcException {
checkInvokers(invokers, invocation);
RpcContext.getContext().setInvokers((List) invokers);
RpcException exception = null;
Result result = null;
// 向所有invoker发起调用，只要有一个异常，则抛出异常
for (Invoker<T> invoker : invokers) {
try {
result = invoker.invoke(invocation);
} catch (RpcException e) {
exception = e;
logger.warn(e.getMessage(), e);
} catch (Throwable e) {
exception = new RpcException(e.getMessage(), e);
logger.warn(e.getMessage(), e);
}
}
if (exception != null) {
throw exception;
}
return result;
}
总结: broadcast 容错，即向所有invoker发起调用（即广播），全部成功才算成功。
3.7. mergeable 归并容错的实现
// org.apache.dubbo.rpc.cluster.support.MergeableClusterInvoker#doInvoke
@Override
protected Result doInvoke(Invocation invocation, List<Invoker<T>> invokers, LoadBalance loadbalance) throws RpcException {
checkInvokers(invokers, invocation);
// merger=xxx
String merger = getUrl().getMethodParameter(invocation.getMethodName(), MERGER_KEY);
// 没有指定merger, 直接调用一个可用 invoker 即可
if (ConfigUtils.isEmpty(merger)) { // If a method doesn't have a merger, only invoke one Group
for (final Invoker<T> invoker : invokers) {
if (invoker.isAvailable()) {
try {
return invoker.invoke(invocation);
} catch (RpcException e) {
if (e.isNoInvokerAvailableAfterFilter()) {
log.debug("No available provider for service" + getUrl().getServiceKey() + " on group " + invoker.getUrl().getParameter(GROUP_KEY) + ", will continue to try another group.");
} else {
throw e;
}
}
}
}
// 最后尝试使用第一个 invoker.invoke()
return invokers.iterator().next().invoke(invocation);
}
Class<?> returnType;
try {
returnType = getInterface().getMethod(
invocation.getMethodName(), invocation.getParameterTypes()).getReturnType();
} catch (NoSuchMethodException e) {
returnType = null;
}
Map<String, Result> results = new HashMap<>();
for (final Invoker<T> invoker : invokers) {
RpcInvocation subInvocation = new RpcInvocation(invocation, invoker);
subInvocation.setAttachment(ASYNC_KEY, "true");
// 异步调用所有 invoker
results.put(invoker.getUrl().getServiceKey(), invoker.invoke(subInvocation));
}
Object result = null;
List<Result> resultList = new ArrayList<Result>(results.size());
for (Map.Entry<String, Result> entry : results.entrySet()) {
Result asyncResult = entry.getValue();
try {
// 等待所有 invoker 的结果响应
Result r = asyncResult.get();
if (r.hasException()) {
log.error("Invoke " + getGroupDescFromServiceKey(entry.getKey()) +
" failed: " + r.getException().getMessage(),
r.getException());
} else {
// 将所有结果放到 resultList 中
resultList.add(r);
}
} catch (Exception e) {
throw new RpcException("Failed to invoke service " + entry.getKey() + ": " + e.getMessage(), e);
}
}
if (resultList.isEmpty()) {
return AsyncRpcResult.newDefaultAsyncResult(invocation);
} else if (resultList.size() == 1) {
// 只有一个结果，则返回一个 Result
return resultList.iterator().next();
}
if (returnType == void.class) {
return AsyncRpcResult.newDefaultAsyncResult(invocation);
}
if (merger.startsWith(".")) {
merger = merger.substring(1);
Method method;
try {
method = returnType.getMethod(merger, returnType);
} catch (NoSuchMethodException e) {
throw new RpcException("Can not merge result because missing method [ " + merger + " ] in class [ " +
returnType.getName() + " ]");
}
if (!Modifier.isPublic(method.getModifiers())) {
method.setAccessible(true);
}
result = resultList.remove(0).getValue();
try {
if (method.getReturnType() != void.class
&& method.getReturnType().isAssignableFrom(result.getClass())) {
for (Result r : resultList) {
result = method.invoke(result, r.getValue());
}
} else {
for (Result r : resultList) {
method.invoke(result, r.getValue());
}
}
} catch (Exception e) {
throw new RpcException("Can not merge result: " + e.getMessage(), e);
}
} else {
Merger resultMerger;
// 解析出 merger, 调用 其 merge 方法，返回结果
if (ConfigUtils.isDefault(merger)) {
resultMerger = MergerFactory.getMerger(returnType);
} else {
resultMerger = ExtensionLoader.getExtensionLoader(Merger.class).getExtension(merger);
}
if (resultMerger != null) {
List<Object> rets = new ArrayList<Object>(resultList.size());
for (Result r : resultList) {
rets.add(r.getValue());
}
// 有很多merger, 都在 org.apache.dubbo.rpc.cluster.merger中，
// 如: MapMerger/Array/Boolean/Int/List/Set/ByteArray...
result = resultMerger.merge(
rets.toArray((Object[]) Array.newInstance(returnType, 0)));
} else {
throw new RpcException("There is no merger to merge result.");
}
}
return AsyncRpcResult.newDefaultAsyncResult(result, invocation);
}
总结: mergeable 容错，依次调用所有invokers, 并通过使用一个merger进行结果合并处理以返回结果。虽然不知道有啥用，但是感觉很厉害的样子。
dubbo的集群容错实现中，使用了 模板方式模式，责任链模式，工厂模式，使得各个容错的实现显得相当简洁明了和简单容易。这就是优秀框架的特性吧。
正文到此结束
- 本文标签： db 安全 Select consumer queue id 类图 node 集群 解析 provider message Collection retry 服务器 cat HTML dubbo 线程池 IO synchronized apache 线程 CTO 总结 ACE executor ArrayList spring tar CEO final http cache HashMap 部署 IDE list ask ORM bug tk 负载均衡 UI value src Service 专心 HashSet https map key build Atom 高可用 并发
- 版权声明： 本文为互联网转载文章，出处已在文章中说明(部分除外)。如果侵权，请联系本站长删除，谢谢。
- 本文海报： 生成海报一 生成海报二
热门推荐
相关文章
近期评论
-
文章和留言都翻到11页了 没有OOM
-
-
朋友，翻页到11页，及以后，会出现OOM，无法访问
-
-
搞个gitee的项目
-
-
版本号是多少，你可以下载哪个代码仓库，jdk选1.8 直接跑就行
-
-
-
Loading...
![[HBLOG]公众号](https://www.liuhaihua.cn/img/qrcode_gzh.jpg)
