Spring Cloud Feign组件

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、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

二、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）

 1 Object executeAndDecode(RequestTemplate template) throws Throwable {
 2     Request request = targetRequest(template);
 3 
 4     if (logLevel != Logger.Level.NONE) {
 5       logger.logRequest(metadata.configKey(), logLevel, request);
 6     }
 7 
 8     Response response;
 9     long start = System.nanoTime();
10     try {
11       response = client.execute(request, options);
12       // ensure the request is set. TODO: remove in Feign 10
13       response.toBuilder().request(request).build();
14     } catch (IOException e) {
15       if (logLevel != Logger.Level.NONE) {
16         logger.logIOException(metadata.configKey(), logLevel, e, elapsedTime(start));
17       }
18       throw errorExecuting(request, e);
19     }
20     long elapsedTime = TimeUnit.NANOSECONDS.toMillis(System.nanoTime() - start);
21 
22     boolean shouldClose = true;
23     try {
24       if (logLevel != Logger.Level.NONE) {
25         response =
26             logger.logAndRebufferResponse(metadata.configKey(), logLevel, response, elapsedTime);
27         // ensure the request is set. TODO: remove in Feign 10
28         response.toBuilder().request(request).build();
29       }
30       if (Response.class == metadata.returnType()) {
31         if (response.body() == null) {
32           return response;
33         }
34         if (response.body().length() == null ||
35                 response.body().length() > MAX_RESPONSE_BUFFER_SIZE) {
36           shouldClose = false;
37           return response;
38         }
39         // Ensure the response body is disconnected
40         byte[] bodyData = Util.toByteArray(response.body().asInputStream());
41         return response.toBuilder().body(bodyData).build();
42       }
43       if (response.status() >= 200 && response.status() < 300) {
44         if (void.class == metadata.returnType()) {
45           return null;
46         } else {
47           return decode(response);
48         }
49       } else if (decode404 && response.status() == 404 && void.class != metadata.returnType()) {
50         return decode(response);
51       } else {
52         throw errorDecoder.decode(metadata.configKey(), response);
53       }
54     } catch (IOException e) {
55       if (logLevel != Logger.Level.NONE) {
56         logger.logIOException(metadata.configKey(), logLevel, e, elapsedTime);
57       }
58       throw errorReading(request, response, e);
59     } finally {
60       if (shouldClose) {
61         ensureClosed(response.body());
62       }
63     }
64   }

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)

 1 @Override
 2     public Response execute(Request request, Request.Options options) throws IOException {
 3         try {
 4             URI asUri = URI.create(request.url());
 5             String clientName = asUri.getHost();
 6             URI uriWithoutHost = cleanUrl(request.url(), clientName);
 7             FeignLoadBalancer.RibbonRequest ribbonRequest = new FeignLoadBalancer.RibbonRequest(
 8                     this.delegate, request, uriWithoutHost);
 9 
10             IClientConfig requestConfig = getClientConfig(options, clientName);
11             return lbClient(clientName).executeWithLoadBalancer(ribbonRequest,
12                     requestConfig).toResponse();
13         }
14         catch (ClientException e) {
15             IOException io = findIOException(e);
16             if (io != null) {
17                 throw io;
18             }
19             throw new RuntimeException(e);
20         }
21     }

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？

  1 public Observable<T> submit(final ServerOperation<T> operation) {
  2         final ExecutionInfoContext context = new ExecutionInfoContext();
  3         
  4         if (listenerInvoker != null) {
  5             try {
  6                 listenerInvoker.onExecutionStart();
  7             } catch (AbortExecutionException e) {
  8                 return Observable.error(e);
  9             }
 10         }
 11 
 12         final int maxRetrysSame = retryHandler.getMaxRetriesOnSameServer();
 13         final int maxRetrysNext = retryHandler.getMaxRetriesOnNextServer();
 14 
 15         // Use the load balancer
 16         Observable<T> o = 
 17                 (server == null ? selectServer() : Observable.just(server))
 18                 .concatMap(new Func1<Server, Observable<T>>() {
 19                     @Override
 20                     // Called for each server being selected
 21                     public Observable<T> call(Server server) {
 22                         context.setServer(server);
 23                         final ServerStats stats = loadBalancerContext.getServerStats(server);
 24                         
 25                         // Called for each attempt and retry
 26                         Observable<T> o = Observable
 27                                 .just(server)
 28                                 .concatMap(new Func1<Server, Observable<T>>() {
 29                                     @Override
 30                                     public Observable<T> call(final Server server) {
 31                                         context.incAttemptCount();
 32                                         loadBalancerContext.noteOpenConnection(stats);
 33                                         
 34                                         if (listenerInvoker != null) {
 35                                             try {
 36                                                 listenerInvoker.onStartWithServer(context.toExecutionInfo());
 37                                             } catch (AbortExecutionException e) {
 38                                                 return Observable.error(e);
 39                                             }
 40                                         }
 41                                         
 42                                         final Stopwatch tracer = loadBalancerContext.getExecuteTracer().start();
 43                                         
 44                                         return operation.call(server).doOnEach(new Observer<T>() {
 45                                             private T entity;
 46                                             @Override
 47                                             public void onCompleted() {
 48                                                 recordStats(tracer, stats, entity, null);
 49                                                 // TODO: What to do if onNext or onError are never called?
 50                                             }
 51 
 52                                             @Override
 53                                             public void onError(Throwable e) {
 54                                                 recordStats(tracer, stats, null, e);
 55                                                 logger.debug("Got error {} when executed on server {}", e, server);
 56                                                 if (listenerInvoker != null) {
 57                                                     listenerInvoker.onExceptionWithServer(e, context.toExecutionInfo());
 58                                                 }
 59                                             }
 60 
 61                                             @Override
 62                                             public void onNext(T entity) {
 63                                                 this.entity = entity;
 64                                                 if (listenerInvoker != null) {
 65                                                     listenerInvoker.onExecutionSuccess(entity, context.toExecutionInfo());
 66                                                 }
 67                                             }                            
 68                                             
 69                                             private void recordStats(Stopwatch tracer, ServerStats stats, Object entity, Throwable exception) {
 70                                                 tracer.stop();
 71                                                 loadBalancerContext.noteRequestCompletion(stats, entity, exception, tracer.getDuration(TimeUnit.MILLISECONDS), retryHandler);
 72                                             }
 73                                         });
 74                                     }
 75                                 });
 76                         
 77                         if (maxRetrysSame > 0) 
 78                             o = o.retry(retryPolicy(maxRetrysSame, true));
 79                         return o;
 80                     }
 81                 });
 82             
 83         if (maxRetrysNext > 0 && server == null) 
 84             o = o.retry(retryPolicy(maxRetrysNext, false));
 85         
 86         return o.onErrorResumeNext(new Func1<Throwable, Observable<T>>() {
 87             @Override
 88             public Observable<T> call(Throwable e) {
 89                 if (context.getAttemptCount() > 0) {
 90                     if (maxRetrysNext > 0 && context.getServerAttemptCount() == (maxRetrysNext + 1)) {
 91                         e = new ClientException(ClientException.ErrorType.NUMBEROF_RETRIES_NEXTSERVER_EXCEEDED,
 92                                 "Number of retries on next server exceeded max " + maxRetrysNext
 93                                 + " retries, while making a call for: " + context.getServer(), e);
 94                     }
 95                     else if (maxRetrysSame > 0 && context.getAttemptCount() == (maxRetrysSame + 1)) {
 96                         e = new ClientException(ClientException.ErrorType.NUMBEROF_RETRIES_EXEEDED,
 97                                 "Number of retries exceeded max " + maxRetrysSame
 98                                 + " retries, while making a call for: " + context.getServer(), e);
 99                     }
100                 }
101                 if (listenerInvoker != null) {
102                     listenerInvoker.onExecutionFailed(e, context.toFinalExecutionInfo());
103                 }
104                 return Observable.error(e);
105             }
106         });
107     }

通过上面代码分析，发现Ribbon和Hystrix一样都是利用了rxjava看来有必要掌握下rxjava了又。这里面比较重要的就是17行，

selectServer() 方法选择指定的Server，负载均衡的策略主要是有ILoadBalancer接口不同实现方式：

BaseLoadBalancer采用的规则为RoundRobinRule 轮训规则

DynamicServerListLoadBalancer继承了BaseLoadBalancer，主要运行时改变Server列表

NoOpLoadBalancer 什么操作都不做

ZoneAwareLoadBalancer 功能主要是根据区域Zone分组的实例列表