【一起学源码-微服务】Feign 源码三:Feign结合Ribbon实现负载均衡的原理分析
一枝花算不算浪漫 人气:1前言
前情回顾
上一讲我们已经知道了Feign的工作原理其实是在项目启动的时候,通过JDK动态代理为每个FeignClinent生成一个动态代理。
动态代理的数据结构是:ReflectiveFeign.FeignInvocationHandler。其中包含target
(里面是serviceName等信息)和dispatcher
(map数据结构,key是请求的方法名,方法参数等,value是SynchronousMethodHandler
)。
如下图所示:
本讲目录
这一讲主要是Feign与Ribbon结合实现负载均衡的原理分析。
说明
原创不易,如若转载 请标明来源!
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源码分析
Feign结合Ribbon实现负载均衡原理
通过前面的分析,我们可以直接来看下SynchronousMethodHandler
中的代码:
final class SynchronousMethodHandler implements MethodHandler {
@Override
public Object invoke(Object[] argv) throws Throwable {
// 生成请求类似于:GET /sayHello/wangmeng HTTP/1.1
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;
}
}
}
Object executeAndDecode(RequestTemplate template) throws Throwable {
// 构建request对象:GET http://serviceA/sayHello/wangmeng HTTP/1.1
Request request = targetRequest(template);
if (logLevel != Logger.Level.NONE) {
logger.logRequest(metadata.configKey(), logLevel, request);
}
Response response;
long start = System.nanoTime();
try {
// 这个client就是之前构建的LoadBalancerFeignClient,options是超时时间
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);
// 下面逻辑都是构建返回值response
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());
}
}
}
}
这里主要是构建request数据,然后通过request和options去通过LoadBalancerFeignClient.execute()
方法去获得返回值。我们可以接着看client端的调用:
public class LoadBalancerFeignClient implements Client {
@Override
public Response execute(Request request, Request.Options options) throws IOException {
try {
// asUri: http://serviceA/sayHello/wangmeng
URI asUri = URI.create(request.url());
// clientName:serviceA
String clientName = asUri.getHost();
// uriWithoutHost: http://sayHello/wangmeng
URI uriWithoutHost = cleanUrl(request.url(), clientName);
// 这里ribbonRequest:GET http:///sayHello/wangmeng HTTP/1.1
FeignLoadBalancer.RibbonRequest ribbonRequest = new FeignLoadBalancer.RibbonRequest(
this.delegate, request, uriWithoutHost);
// 这里面config只有两个超时时间,一个是connectTimeout:5000,一个是readTimeout:5000
IClientConfig requestConfig = getClientConfig(options, clientName);
// 真正执行负载均衡的地方
return lbClient(clientName).executeWithLoadBalancer(ribbonRequest,
requestConfig).toResponse();
}
catch (ClientException e) {
IOException io = findIOException(e);
if (io != null) {
throw io;
}
throw new RuntimeException(e);
}
}
}
接着我们看下lbClient()
和executeWithLoadBalancer()
public class LoadBalancerFeignClient implements Client {
private FeignLoadBalancer lbClient(String clientName) {
return this.lbClientFactory.create(clientName);
}
}
public class CachingSpringLoadBalancerFactory {
public FeignLoadBalancer create(String clientName) {
if (this.cache.containsKey(clientName)) {
return this.cache.get(clientName);
}
IClientConfig config = this.factory.getClientConfig(clientName);
// 获取Ribbon ILoadBalancer信息
ILoadBalancer lb = this.factory.getLoadBalancer(clientName);
ServerIntrospector serverIntrospector = this.factory.getInstance(clientName, ServerIntrospector.class);
FeignLoadBalancer client = enableRetry ? new RetryableFeignLoadBalancer(lb, config, serverIntrospector,
loadBalancedRetryPolicyFactory, loadBalancedBackOffPolicyFactory, loadBalancedRetryListenerFactory) : new FeignLoadBalancer(lb, config, serverIntrospector);
this.cache.put(clientName, client);
return client;
}
}
这里是获取了ILoadBalancer
数据,里面包含了Ribbon获取的serviceA所有服务节点信息。
这里已经获取到ILoadBalancer
,里面包含serviceA服务器所有节点请求host信息。接下来就是从中负载均衡选择一个节点信息host出来。
public abstract class AbstractLoadBalancerAwareClient<S extends ClientRequest, T extends IResponse> extends LoadBalancerContext implements IClient<S, T>, IClientConfigAware {
public T executeWithLoadBalancer(final S request, final IClientConfig requestConfig) throws ClientException {
LoadBalancerCommand<T> command = buildLoadBalancerCommand(request, requestConfig);
try {
return command.submit(
new ServerOperation<T>() {
@Override
public Observable<T> call(Server server) {
URI finalUri = reconstructURIWithServer(server, request.getUri());
S requestForServer = (S) request.replaceUri(finalUri);
try {
return Observable.just(AbstractLoadBalancerAwareClient.this.execute(requestForServer, requestConfig));
}
catch (Exception e) {
return Observable.error(e);
}
}
})
.toBlocking()
.single();
} catch (Exception e) {
Throwable t = e.getCause();
if (t instanceof ClientException) {
throw (ClientException) t;
} else {
throw new ClientException(e);
}
}
}
}
public class LoadBalancerCommand<T> {
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>>() {
}
// 省略代码...
// selectServer是真正执行负载均衡的逻辑
private Observable<Server> selectServer() {
return Observable.create(new OnSubscribe<Server>() {
@Override
public void call(Subscriber<? super Server> next) {
try {
// loadBalancerURI是http:///sayHello/wangmeng, loadBalancerKey为null
Server server = loadBalancerContext.getServerFromLoadBalancer(loadBalancerURI, loadBalancerKey);
next.onNext(server);
next.onCompleted();
} catch (Exception e) {
next.onError(e);
}
}
});
}
}
public class LoadBalancerContext implements IClientConfigAware {
public Server getServerFromLoadBalancer(@Nullable URI original, @Nullable Object loadBalancerKey) throws ClientException {
String host = null;
int port = -1;
if (original != null) {
host = original.getHost();
}
if (original != null) {
Pair<String, Integer> schemeAndPort = deriveSchemeAndPortFromPartialUri(original);
port = schemeAndPort.second();
}
// 获取到ILoadBalancer,这里面有IRule的信息及服务节点所有信息
ILoadBalancer lb = getLoadBalancer();
if (host == null) {
// Partial URI or no URI Case
// well we have to just get the right instances from lb - or we fall back
if (lb != null){
// 这里就执行真正的chooseServer的逻辑了。默认的rule为ZoneAvoidanceZule
Server svc = lb.chooseServer(loadBalancerKey);
if (svc == null){
throw new ClientException(ClientException.ErrorType.GENERAL,
"Load balancer does not have available server for client: "
+ clientName);
}
host = svc.getHost();
if (host == null){
throw new ClientException(ClientException.ErrorType.GENERAL,
"Invalid Server for :" + svc);
}
logger.debug("{} using LB returned Server: {} for request {}", new Object[]{clientName, svc, original});
return svc;
}
// 省略代码
}
}
}
上面代码已经很清晰了,这里就是真正的通过ribbon的 rule.chooseServer()
负载均衡地选择了一个服务节点调用,debug如下:
到了这里feign与ribbon的分析也就结束了,返回请求url信息,然后得到response结果:
总结
上面已经分析了Feign与Ribbon的整合,最终还是落到Ribbon中的ILoadBalancer中,使用最后使用IRule去选择对应的server数据。
下一讲 会画一个很大的图,包含Feign、Ribbon、Eureka关联的图,里面会画出每个组件的细节及依赖关系。也算是学习至今的一个总复习了。
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