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| |
| <h2 id="producer">简单同步模式的Producer：</h2> |
| <p>示例代码：</p> |
| <pre><code class="language-java">@GetMapping(path = "/hello/{name}") |
| public String hello(@PathVariable(name = "name") String name){ |
| return "hello " + name; |
| } |
| </code></pre> |
| <p>与此对应的处理流程如下：</p> |
| <p><img alt="" src="../assets/reactive/normalSync.png" /></p> |
| <p>这是传统典型的工作模型，核心思想是不阻塞网络线程，将业务放在独立的线程中处理（为了简化表达，executor中只画一个线程）</p> |
| <p>一般情况下，此模式问题不大。</p> |
| <h2 id="_1">嵌套同步调用：</h2> |
| <p>不是所有的业务都是简单处理一下，就可以直接应答，可能还需要调用其他微服务.</p> |
| <p>示例代码：</p> |
| <pre><code class="language-java">public interface Intf{ |
| String hello(String name); |
| } |
| |
| @GetMapping(path = "/hello/{name}") |
| public String hello(@PathVariable(name = "name") String name){ |
| return "from remote: hello " + intf.hello(name); |
| } |
| </code></pre> |
| <p>与此对应的处理流程如下：</p> |
| <p><img alt="" src="../assets/reactive/nestedSync.png" /></p> |
| <p>根据这个流程的特点，可以看到会产生以下结果：</p> |
| <ul> |
| <li> |
| <p>因为是同步调用，在“Other microservices”未应答之前“Microservice A”的调用线程一直处于阻塞等待状态，不处理任何其他事务</p> |
| </li> |
| <li> |
| <p>当Executor中所有线程都在等待远程应答时，所有新的请求都只能在Queue中排队，得不到处理，此时整个系统相当于停止工作了</p> |
| </li> |
| <li> |
| <p>要增加处理能力，只能增加Executor中的线程数，而操作系统并不能无限地增加线程数，事实上增加线程数带来的收益是一个抛物线模型，超出一定的临界值后，系统的处理能力其实会下降，而这个临界值并不会太大</p> |
| </li> |
| <li> |
| <p>当业务逻辑中，需要多次进行远程同步操作时，会更加恶化这个现象</p> |
| </li> |
| </ul> |
| <h2 id="_2">嵌套同步调用的“错误”优化：</h2> |
| <p>针对前一场景，有人会认为将“Invoke producer method”丢进另一个线程池，可以解决问题，包括以下处理方式：</p> |
| <ul> |
| <li> |
| <p>在producer method打标注@Async，由AOP负责将对该方法的调用丢进其他线程池去</p> |
| </li> |
| <li> |
| <p>在producer method内部通过业务代码转移线程</p> |
| </li> |
| </ul> |
| <p>形成以下流程：</p> |
| <p><img alt="" src="../assets/reactive/wrongSyncOptimization.png" /></p> |
| <p>根据这个流程的特点，可以看到会产生以下结果：</p> |
| <ul> |
| <li> |
| <p>“Invoke producer method”必须立即返回，否则Executor线程还是得不到释放</p> |
| </li> |
| <li> |
| <p>“Invoke producer method”必须提供一个新的机制告知调用流程自己的返回值，不是最终返回值（当前没有这个机制）</p> |
| </li> |
| <li> |
| <p>虽然Executor线程释放了，但是Customer Executor，其实还是阻塞住，在等待远端应答，整个系统的阻塞状态并没有得到改变；而且还凭空多了一次线程切换</p> |
| </li> |
| <li> |
| <p>该机制看上去，唯一的作用，是释放了executor线程，让executor线程有机会处理其他请求，这相当于隔离仓的概念，处理速度慢的业务不要影响其他业务；但是这个概念serviceComb是可以直接支持的，可以配置指定的业务方法独占全新的executor，这样整个流程就跟“嵌套同步调用”完全一样，流程更简单，而不需要在“Invoke producer method”层次来做这个事情</p> |
| </li> |
| </ul> |
| <h2 id="reactive">纯Reactive机制</h2> |
| <p>示例代码：</p> |
| <pre><code class="language-java">public interface Intf{ |
| CompletableFuture<String> hello(String name); |
| } |
| |
| @GetMapping(path = "/hello/{name}") |
| public CompletableFuture<String> hello(@PathVariable(name = "name") String name){ |
| CompletableFuture<String> future = new CompletableFuture<>(); |
| intf.hello(name).whenComplete((result, exception) -> { |
| if (exception == null) { |
| future.complete("from remote: " + result); |
| return; |
| } |
| |
| future.completeExceptionally(exception); |
| }); |
| return future; |
| } |
| </code></pre> |
| <p>与此对应的处理流程如下：</p> |
| <p><img alt="" src="../assets/reactive/pureReactive.png" /></p> |
| <ul> |
| <li> |
| <p>与传统流程不同的是，所有功能都在eventloop中执行，并不会进行线程切换</p> |
| </li> |
| <li> |
| <p>橙色箭头走完后，对本线程的占用即完成了，不会阻塞等待应答，该线程可以处理其他任务</p> |
| </li> |
| <li> |
| <p>当收到远端应答后，由网络数据驱动开始走红色箭头的应答流程</p> |
| </li> |
| <li> |
| <p>只要有任务，线程就不会停止，会一直执行任务，可以充分利用cpu资源，也不会产生多余的线程切换，去无谓地消耗cpu。</p> |
| </li> |
| </ul> |
| <p>因为同步模式下，需要大量的线程来提升并发度，而大量的线程又带来线程切换的额外消耗。</p> |
| <p>测试数据表明，reactive模式，只需要消耗同步模式不到一半的cpu，即可达到或超过同步模式的tps，并且时延更低。</p> |
| <h2 id="reactive_1">混合Reactive机制</h2> |
| <p>Reactvie要求：所有在eventloop中执行的逻辑，不允许有任何的阻塞动作，包括不限于wait、sleep、巨大循环、同步查询DB等等。</p> |
| <p>serviceComb底层是基于vertx的，vertx生态中有jdbc、mq、zooKeeper等等各种丰富组件的reactive驱动，一般情况下都可以满足要求。</p> |
| <p>但是有的场景下，确实有的同步操作无法避免，比如：</p> |
| <ul> |
| <li> |
| <p>私有的安全加固的redis，只提供了同步驱动</p> |
| </li> |
| <li> |
| <p>较复杂的业务运算</p> |
| </li> |
| <li> |
| <p>……</p> |
| </li> |
| </ul> |
| <p>此时，可以将这些同步的逻辑抽取出来放到线程池中去处理，而其他部分仍然使用reactive的流程。</p> |
| <h2 id="reactive_2">关于reactive的一些说明：</h2> |
| <ul> |
| <li> |
| <p>Producer：</p> |
| </li> |
| <li> |
| <p>producer是否使用reactive与consumer如何调用，没有任何联系</p> |
| </li> |
| <li> |
| <p>当operation返回值为CompletableFuture类型时，默认此operation工作于reactive模式，此时如果需要强制此operation工作于线程池模式，需要在microservice.yaml中明确配置；假设某operation，其schemaId为sid，operationId为asyncQuery，则需要进行以下配置：</p> |
| </li> |
| </ul> |
| <pre><code>servicecomb: |
| executors: |
| Provider: |
| sid.asyncQuery: cse.executor.groupThreadPool |
| </code></pre> |
| <p>这里的cse.executor.groupThreadPool是serviceComb内置的默认线程池，用户可以任意指定为自己的定制线程池。</p> |
| <ul> |
| <li> |
| <p>Consumer：</p> |
| </li> |
| <li> |
| <p>consumer是否使用reactive与producer如何实现，没有任何联系</p> |
| </li> |
| <li> |
| <p>当前只支持透明RPC模式，使用JDK原生的CompletableFuture来承载此功能</p> |
| <p>completableFuture的when、then等等功能都可直接使用</p> |
| <p>但是completableFuture的async系列功能，其实是另外启线程池来执行功能，不建议使用</p> |
| <p>关于RxJava Observable的支持后续会加入</p> |
| <p>关于AsyncRestTemplate的支持后续会加入</p> |
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