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2023-07-11
Spring Cloud Feign组件实例解析
这篇文章主要介绍了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 {
returnhttp:// 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
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
(server == null ? selectServer() : Observable.just(server))
.concatMap(new Func1
@Override
// Called for each server being selected
public Observable
context.setServer(server);
final ServerStats stats = loadBalancerContext.getServerStats(server);
// Called for each attempt and retry
Observable
.just(server)
.concatMap(new Func1
@Override
public Observable
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
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
@Override
public Observable
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.getEmpYUServer(), 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);
}
});
}
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
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