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1、Spring MVC堵塞式编程中的技术方案

a） 最简单的方案，使用 DeferredResult 代码如下，

import lombok.RequiredArgsConstructor;
import lombok.extern.slf4j.Slf4j;
import org.springframework.web.bind.annotation.*;
import org.springframework.web.context.request.async.DeferredResult;import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;@Slf4j
@RestController()
@RequestMapping("/v1/defered")
@RequiredArgsConstructor
public class DeferredResultController {// 延迟执行服务private ExecutorService executorService = Executors.newSingleThreadExecutor();@PostMapping("/test")public DeferredResult<String> simpleTest() {// 1. 创建DeferredResult对象DeferredResult<String> deferredResult = new DeferredResult<>(1000L);// 2. 设置超时回调，当DeferredResult超时后，会执行这个回调函数deferredResult.onTimeout(() -> {log.info("DeferredResult超时了");deferredResult.setResult("延迟!");});// 延迟2秒钟执行executorService.submit(() -> {try {Thread.sleep(2000);} catch (InterruptedException e) {throw new RuntimeException(e);}log.info("执行结果:{}", deferredResult.getResult());deferredResult.setResult("hello world1");});return deferredResult;}}

代码解读：

1. 创建DeferredResult对象，该对象默认设置了1s的超时时间，
2. 设置超时回调，如果在1秒钟内未回调结果，那么则执行 onTimeout的回调函数。
3. 模拟执行一个异步线程，2秒之后再执行结果。

最终控制台输出如下。

DeferredResult超时了
执行结果:延迟!

会发现，最后超时之后，仍然会执行成功，不过deferredResult里面的结果被填充。

用户收到的结果

延迟!

b) 上点难度，使用redis监听事件，根据事件的不同返回不同的数据值

1. 首先配置data.redis框架中的RedisTemplate模板以及RedisMessageListenerContainer(监听容器)

import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.data.redis.connection.RedisConnectionFactory;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.data.redis.listener.RedisMessageListenerContainer;
import org.springframework.data.redis.serializer.StringRedisSerializer;@Configuration
public class MyRedisConfig {@Beanpublic RedisTemplate<String, String> redisTemplate(RedisConnectionFactory factory) {RedisTemplate<String, String> template = new RedisTemplate<>();template.setConnectionFactory(factory);template.setKeySerializer(new StringRedisSerializer());template.setValueSerializer(new StringRedisSerializer());template.setHashKeySerializer(new StringRedisSerializer());template.setHashValueSerializer(new StringRedisSerializer());template.afterPropertiesSet();return template;}@Beanpublic RedisMessageListenerContainer redisMessageListenerContainer(RedisConnectionFactory factory) {RedisMessageListenerContainer container = new RedisMessageListenerContainer();container.setConnectionFactory(factory);return container;}
}

2. 编写异步转同步方法。

import lombok.RequiredArgsConstructor;
import lombok.extern.slf4j.Slf4j;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.data.redis.connection.Message;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.data.redis.listener.ChannelTopic;
import org.springframework.data.redis.listener.RedisMessageListenerContainer;
import org.springframework.data.redis.connection.MessageListener;
import org.springframework.web.bind.annotation.*;
import org.springframework.web.context.request.async.DeferredResult;import java.util.Map;
import java.util.concurrent.ConcurrentHashMap;@Slf4j
@RestController()
@RequestMapping("/v1/redis/defered")
@RequiredArgsConstructor
public class DeferredResultRedisController {@Autowiredprivate RedisTemplate<String, String> redisTemplate2;@Autowiredprivate RedisMessageListenerContainer container;private final Map<String, DeferredResult<String>> deferredResults = new ConcurrentHashMap<>();private final Map<String, MessageListener> listeners = new ConcurrentHashMap<>();@GetMapping("/async/subscribe/{channel}")public DeferredResult<String> subscribe(@PathVariable String channel) {DeferredResult<String> result = new DeferredResult<>(20000l, "Timeout6666");String channelName = "channel:" + channel;deferredResults.put(channelName, result);// 创建消息监听器MessageListener listener = new MessageListener() {@Overridepublic void onMessage(Message message, byte[] pattern) {String receivedChannel = new String(message.getChannel());String msg;try {// 模拟可能抛出异常的处理msg = parseMessage(message.getBody());} catch (Exception e) {// 手动设置错误结果result.setErrorResult("Message parsing failed: " + e.getMessage());return;}if (receivedChannel.equals(channelName)) {DeferredResult<String> deferred = deferredResults.remove(channelName);if (deferred != null) {deferred.setResult(msg);}container.removeMessageListener(this);listeners.remove(channelName);}}private String parseMessage(byte[] body) throws Exception {// 模拟解析错误if (body == null) {throw new IllegalArgumentException("Message body is null");}return new String(body);}};// 添加监听器try {container.addMessageListener(listener, new ChannelTopic(channelName));listeners.put(channelName, listener);} catch (Exception e) {// Redis 连接异常result.setErrorResult("Failed to subscribe: " + e.getMessage());}// 处理异步异常result.onError(throwable -> {System.err.println("Async error for channel " + channelName + ": " + throwable.getMessage());releaseResource(channelName);// 可选：设置默认错误响应result.setErrorResult("Error: " + throwable.getMessage());});// 清理订阅result.onCompletion(() -> {log.info("Async complete for channel " + channelName);releaseResource(channelName);});result.onTimeout(() -> {log.info("Async timed out for channel " + channelName);releaseResource(channelName);});return result;}private void releaseResource(String channelName) {deferredResults.remove(channelName);MessageListener l = listeners.remove(channelName);if (l != null) {container.removeMessageListener(l);}}@PostMapping("/publish/{channel}")public String publish(@PathVariable String channel, @RequestBody String message) {redisTemplate2.convertAndSend("channel:" + channel, message);return "Published to channel: " + channel;}}

步骤流程

c) 单节点简单方案。使用spring event

只涉及核心代码

@RestController
public class AsyncEventController {private final ApplicationEventPublisher eventPublisher;private final Map<String, DeferredResult<String>> deferredResults = new ConcurrentHashMap<>();public AsyncEventController(ApplicationEventPublisher eventPublisher) {this.eventPublisher = eventPublisher;}// 异步请求@GetMapping("/async/event/{id}")public DeferredResult<String> asyncRequest(@PathVariable String id) {DeferredResult<String> result = new DeferredResult<>(30000L, "Timeout");deferredResults.put(id, result);// 模拟异步任务，发布事件eventPublisher.publishEvent(new CustomEvent(id, "Processed data for " + id));result.onCompletion(() -> deferredResults.remove(id));result.onTimeout(() -> deferredResults.remove(id));result.onError(throwable -> {System.err.println("Error for " + id + ": " + throwable.getMessage());deferredResults.remove(id);});return result;}// 事件监听器@Async@EventListenerpublic void handleEvent(CustomEvent event) {DeferredResult<String> result = deferredResults.remove(event.getId());if (result != null) {result.setResult(event.getData());}}
}// 自定义事件类
class CustomEvent extends ApplicationEvent {private final String id;private final String data;public CustomEvent(String id, String data) {super(id);this.id = id;this.data = data;}public String getId() {return id;}public String getData() {return data;}
}

c.1 ) 使用kafka、rockmq等消息队列监听实现。实现类似于spring event，此时代码略。

这里有个非常重要的问题，如果使用的是kafka监听事件，但是节点是多节点，如何保证接收到的事件所在的节点是发起ReferredResult回调的节点。

我们知道kafka监听事件的时候如果是非广播模式的话，那么消费的信息可能在任一节点中，如何保证消费的数据是在一个节点上的呢？可以使用如下的技术方方案，通过 nodeID与lisenterId进行关联，消费到的时候不属于当前节点，那么转发请求到指定节点。

@KafkaListener(topics = "response-topic", groupId = "my-group")public void receiveMessage(String message, String key) {// 解析消息，格式为 nodeId:messageString[] parts = message.split(":", 2);String targetNodeId = parts[0];String data = parts[1];if (targetNodeId.equals(nodeId)) {// 当前节点处理DeferredResult<String> result = deferredResults.remove(key);if (result != null) {result.setResult(data);}requestNodeMap.remove(key);} else {// 转发到目标节点（假设通过 HTTP）forwardToNode(targetNodeId, key, data);}}private void forwardToNode(String targetNodeId, String requestId, String data) {// 假设通过 HTTP 转发到目标节点// 示例：RestTemplate 调用目标节点的 /internal/callback/{requestId}// 实际实现需要节点地址映射（如通过服务发现）// restTemplate.postForObject("http://" + targetNodeId + "/internal/callback/" + requestId, data, String.class);System.out.println("Forwarding to node: " + targetNodeId + ", requestId: " + requestId + ", data: " + data);}

节点标识 + 转发：通过 HTTP 或 Kafka 转发消息，灵活但有额外开销。

那么在多节点环境中，使用 Kafka 监听事件并触发 DeferredResult 延迟结果 回调，需要解决消息到正确节点的路由问题，还有其他的两种方案：
Kafka 分区分配：通过分区键将消息路由到目标节点，效率最高。
共享存储：使用 Redis 或数据库存储请求和节点映射，简单可靠。

方案可能还有更多，比如使用zookeep去做，那么方案很多，适合自己的才是最好的。