Spring Cloud Feign组件实例解析

Z时代
2024-01-10
分类：综合

这篇文章主要介绍了Spring Cloud" title="Spring Cloud">Spring Cloud Feign组件实例解析,文中通过示例代码介绍的非常详细，对大家的学习或者工作具有一定的参考学习价值,需要的朋友可以参考下

采用Spring Cloud微服务框架后，经常会涉及到服务间调用，服务间调用采用了Feign组件。

由于之前有使用dubbo经验。dubbo的负载均衡策略（轮训、最小连接数、随机轮训、加权轮训），dubbo失败策略（快速失败、失败重试等等），

所以Feign负载均衡策略的是什么？失败后是否会重试，重试策略又是什么？带这个疑问，查了一些资料，最后还是看了下代码。毕竟代码就是一切

Spring boot集成Feign的大概流程：

1、利用FeignAutoConfiguration自动配置。并根据EnableFeignClients 自动注册产生Feign的代理类。

2、注册方式利用FeignClientFactoryBean，熟悉Spring知道FactoryBean 产生bean的工厂，有个重要方法getObject产生FeignClient容器bean

3、同时代理类中使用hystrix做资源隔离，Feign代理类中构造 RequestTemplate ，RequestTemlate要做的向负载均衡选中的server发送http请求，并进行编码和解码一系列操作。

下面只是粗略的看了下整体流程，先有整体再有细节吧，下面利用IDEA看下细节：

一、Feign失败重试

SynchronousMethodHandler的方法中的处理逻辑：


@Override
 public Object invoke(Object[] argv) throws Throwable {
  RequestTemplate template = buildTemplateFromArgs.create(argv);
  Retryer retryer = this.retryer.clone();
  while (true) {
   try {
    return executeAndDecode(template);
   } catch (RetryableException e) {
    retryer.continueOrPropagate(e);
    if (logLevel != Logger.Level.NONE) {
     logger.logRetry(metadata.configKey(), logLevel);
    }
    continue;
   }
  }
 }

上面的逻辑很简单。构造 template 并去进行服务间的http调用，然后对返回结果进行解码

当抛出 RetryableException 后，异常逻辑是否重试？重试多少次？带这个问题，看了retryer.continueOrPropagate(e);

具体逻辑如下：


public void continueOrPropagate(RetryableException e) {
   if (attempt++ >= maxAttempts) {
    throw e;
   }
   long interval;
   if (e.retryAfter() != null) {
    interval = e.retryAfter().getTime() - currentTimeMillis();
    if (interval > maxPeriod) {
     interval = maxPeriod;
    }
    if (interval < 0) {
     return;
    }
   } else {
    interval = nextMaxInterval();
   }
   try {
    Thread.sleep(interval);
   } catch (InterruptedException ignored) {
    Thread.currentThread().interrupt();
   }
   sleptForMillis += interval;
  }

当重试次数大于默认次数5时候，直接抛出异常，不在重试

否则每隔一段时间默认值最大1ms 后重试一次。

这就Feign这块的重试这块的粗略逻辑，由于之前工作中一直使用dubbo。同样是否需要将生产环境中重试操作关闭？

思考：之前dubbo生产环境的重试操作都会关闭。原因有几个：

一般第一次失败，重试也会失败，极端情况下不断的重试，会占用大量dubbo连接池，造成连接池被打满，影响核心功能

也是比较重要的一点原因，重试带来的业务逻辑的影响，即如果接口不是幂等的，重试会带来业务逻辑的错误，引发问题

二、Feign负载均衡策略

那么负载均衡的策略又是什么呢？由上图中可知 executeAndDecode（template）


Object executeAndDecode(RequestTemplate template) throws Throwable {
  Request request = targetRequest(template);
  if (logLevel != Logger.Level.NONE) {
   logger.logRequest(metadata.configKey(), logLevel, request);
  }
  Response response;
  long start = System.nanoTime();
  try {
   response = client.execute(request, options);
   // ensure the request is set. TODO: remove in Feign 10
   response.toBuilder().request(request).build();
  } catch (IOException e) {
   if (logLevel != Logger.Level.NONE) {
    logger.logIOException(metadata.configKey(), logLevel, e, elapsedTime(start));
   }
   throw errorExecuting(request, e);
  }
  long elapsedTime = TimeUnit.NANOSECONDS.toMillis(System.nanoTime() - start);
  boolean shouldClose = true;
  try {
   if (logLevel != Logger.Level.NONE) {
    response =
      logger.logAndRebufferResponse(metadata.configKey(), logLevel, response, elapsedTime);
    // ensure the request is set. TODO: remove in Feign 10
    response.toBuilder().request(request).build();
   }
   if (Response.class == metadata.returnType()) {
    if (response.body() == null) {
     return response;
    }
    if (response.body().length() == null ||
        response.body().length() > MAX_RESPONSE_BUFFER_SIZE) {
     shouldClose = false;
     return response;
    }
    // Ensure the response body is disconnected
    byte[] bodyData = Util.toByteArray(response.body().asInputStream());
    return response.toBuilder().body(bodyData).build();
   }
   if (response.status() >= 200 && response.status() < 300) {
    if (void.class == metadata.returnType()) {
     return null;
    } else {
     return decode(response);
    }
   } else if (decode404 && response.status() == 404 && void.class != metadata.returnType()) {
    return decode(response);
   } else {
    throw errorDecoder.decode(metadata.configKey(), response);
   }
  } catch (IOException e) {
   if (logLevel != Logger.Level.NONE) {
    logger.logIOException(metadata.configKey(), logLevel, e, elapsedTime);
   }
   throw errorReading(request, response, e);
  } finally {
   if (shouldClose) {
    ensureClosed(response.body());
   }
  }
 }

概括的说主要做了两件事：发送HTTP请求，解码响应数据

想看的负载均衡应该在11行 response = client.execute(request, options); 而client的实现方式有两种 Default、LoadBalancerFeignClient

猜的话应该是LoadBalancerFeignClient，带这个问题去看源码（其实个人更喜欢带着问题看源码，没有目的一是看很难将复杂的源码关联起来，二是很容易迷失其中）

果然通过一番查找发现 Client 实例就是LoadBalancerFeignClient，而设置这个Client就是通过上面说的FeignClientFactoryBean的getObject方法中设置的，具体不说了

下面重点看LoadBalancerFeignClient execute(request, options)


@Override
  public Response execute(Request request, Request.Options options) throws IOException {
    try {
      URI asUri = URI.create(request.url());
      String clientName = asUri.getHost();
      URI uriWithoutHost = cleanUrl(request.url(), clientName);
      FeignLoadBalancer.RibbonRequest ribbonRequest = new FeignLoadBalancer.RibbonRequest(
          this.delegate, request, uriWithoutHost);
      IClientConfig requestConfig = getClientConfig(options, clientName);
      return lbClient(clientName).executeWithLoadBalancer(ribbonRequest,
          requestConfig).toResponse();
    }
    catch (ClientException e) {
      IOException io = findIOException(e);
      if (io != null) {
        throw io;
      }
      throw new RuntimeException(e);
    }
  }

通过几行代码比较重要的点RibbonRequest ，原来Feign负载均衡还是通过Ribbon实现的，那么Ribbo又是如何实现负载均衡的呢？


public Observable<T> submit(final ServerOperation<T> operation) {
    final ExecutionInfoContext context = new ExecutionInfoContext();
    if (listenerInvoker != null) {
      try {
        listenerInvoker.onExecutionStart();
      } catch (AbortExecutionException e) {
        return Observable.error(e);
      }
    }
    final int maxRetrysSame = retryHandler.getMaxRetriesOnSameServer();
    final int maxRetrysNext = retryHandler.getMaxRetriesOnNextServer();
    // Use the load balancer
    Observable<T> o = 
        (server == null ? selectServer() : Observable.just(server))
        .concatMap(new Func1<Server, Observable<T>>() {
          @Override
          // Called for each server being selected
          public Observable<T> call(Server server) {
            context.setServer(server);
            final ServerStats stats = loadBalancerContext.getServerStats(server);
            // Called for each attempt and retry
            Observable<T> o = Observable
                .just(server)
                .concatMap(new Func1<Server, Observable<T>>() {
                  @Override
                  public Observable<T> call(final Server server) {
                    context.incAttemptCount();
                    loadBalancerContext.noteOpenConnection(stats);
                    if (listenerInvoker != null) {
                      try {
                        listenerInvoker.onStartWithServer(context.toExecutionInfo());
                      } catch (AbortExecutionException e) {
                        return Observable.error(e);
                      }
                    }
                    final Stopwatch tracer = loadBalancerContext.getExecuteTracer().start();
                    return operation.call(server).doOnEach(new Observer<T>() {
                      private T entity;
                      @Override
                      public void onCompleted() {
                        recordStats(tracer, stats, entity, null);
                        // TODO: What to do if onNext or onError are never called?
                      }
                      @Override
                      public void onError(Throwable e) {
                        recordStats(tracer, stats, null, e);
                        logger.debug("Got error {} when executed on server {}", e, server);
                        if (listenerInvoker != null) {
                          listenerInvoker.onExceptionWithServer(e, context.toExecutionInfo());
                        }
                      }
                      @Override
                      public void onNext(T entity) {
                        this.entity = entity;
                        if (listenerInvoker != null) {
                          listenerInvoker.onExecutionSuccess(entity, context.toExecutionInfo());
                        }
                      }              
                      private void recordStats(Stopwatch tracer, ServerStats stats, Object entity, Throwable exception) {
                        tracer.stop();
                        loadBalancerContext.noteRequestCompletion(stats, entity, exception, tracer.getDuration(TimeUnit.MILLISECONDS), retryHandler);
                      }
                    });
                  }
                });
            if (maxRetrysSame > 0) 
              o = o.retry(retryPolicy(maxRetrysSame, true));
            return o;
          }
        });
    if (maxRetrysNext > 0 && server == null) 
      o = o.retry(retryPolicy(maxRetrysNext, false));
    return o.onErrorResumeNext(new Func1<Throwable, Observable<T>>() {
      @Override
      public Observable<T> call(Throwable e) {
        if (context.getAttemptCount() > 0) {
          if (maxRetrysNext > 0 && context.getServerAttemptCount() == (maxRetrysNext + 1)) {
            e = new ClientException(ClientException.ErrorType.NUMBEROF_RETRIES_NEXTSERVER_EXCEEDED,
                "Number of retries on next server exceeded max " + maxRetrysNext
                + " retries, while making a call for: " + context.getServer(), e);
          }
          else if (maxRetrysSame > 0 && context.getAttemptCount() == (maxRetrysSame + 1)) {
            e = new ClientException(ClientException.ErrorType.NUMBEROF_RETRIES_EXEEDED,
                "Number of retries exceeded max " + maxRetrysSame
                + " retries, while making a call for: " + context.getServer(), e);
          }
        }
        if (listenerInvoker != null) {
          listenerInvoker.onExecutionFailed(e, context.toFinalExecutionInfo());
        }
        return Observable.error(e);
      }
    });
  }