自定义spring kafka consumer 线程池

序

本文讲述一下如何自定义spring kafka的consumer线程池

KafkaMessageListenerContainer

spring-kafka-1.2.3.RELEASE-sources.jar!/org/springframework/kafka/listener/KafkaMessageListenerContainer.java

protected void doStart() {
        if (isRunning()) {
            return;
        }
        ContainerProperties containerProperties = getContainerProperties();

        if (!this.consumerFactory.isAutoCommit()) {
            AckMode ackMode = containerProperties.getAckMode();
            if (ackMode.equals(AckMode.COUNT) || ackMode.equals(AckMode.COUNT_TIME)) {
                Assert.state(containerProperties.getAckCount() > 0, "'ackCount' must be > 0");
            }
            if ((ackMode.equals(AckMode.TIME) || ackMode.equals(AckMode.COUNT_TIME))
                    && containerProperties.getAckTime() == 0) {
                containerProperties.setAckTime(5000);
            }
        }

        Object messageListener = containerProperties.getMessageListener();
        Assert.state(messageListener != null, "A MessageListener is required");
        if (messageListener instanceof GenericAcknowledgingMessageListener) {
            this.acknowledgingMessageListener = (GenericAcknowledgingMessageListener<?>) messageListener;
        }
        else if (messageListener instanceof GenericMessageListener) {
            this.listener = (GenericMessageListener<?>) messageListener;
        }
        else {
            throw new IllegalStateException("messageListener must be 'MessageListener' "
                    + "or 'AcknowledgingMessageListener', not " + messageListener.getClass().getName());
        }
        if (containerProperties.getConsumerTaskExecutor() == null) {
            SimpleAsyncTaskExecutor consumerExecutor = new SimpleAsyncTaskExecutor(
                    (getBeanName() == null ? "" : getBeanName()) + "-C-");
            containerProperties.setConsumerTaskExecutor(consumerExecutor);
        }
        if (containerProperties.getListenerTaskExecutor() == null) {
            SimpleAsyncTaskExecutor listenerExecutor = new SimpleAsyncTaskExecutor(
                    (getBeanName() == null ? "" : getBeanName()) + "-L-");
            containerProperties.setListenerTaskExecutor(listenerExecutor);
        }
        this.listenerConsumer = new ListenerConsumer(this.listener, this.acknowledgingMessageListener);
        setRunning(true);
        this.listenerConsumerFuture = containerProperties
                .getConsumerTaskExecutor()
                .submitListenable(this.listenerConsumer);
    }

这里涉及到了两个线程池，一个是ConsumerTaskExecutor，一个是ListenerTaskExecutor，都在containerProperties里头配置
若是没有默认配置，则分别建立带"-C-"和"-L-"的SimpleAsyncTaskExecutor
ConsumerTaskExecutor用来去poll kafka消息
ListenerTaskExecutor用来调用@KafkaListener标注的方法

自定义

自定义executor，将其托管给spring容器的好处就是能够跟随容器的生命周期，在容器销毁以前优雅关闭线程池

扩展ConcurrentKafkaListenerContainerFactory

能够重写spring-kafka-1.2.3.RELEASE-sources.jar!/org/springframework/kafka/config/ConcurrentKafkaListenerContainerFactory.java的initializeContainer方法，而后进行设置

public class CustomConcurrentKafkaListenerContainerFactory<K,V> extends ConcurrentKafkaListenerContainerFactory<K,V> {

    /**
     * The executor for threads that poll the consumer.
     */
    private AsyncListenableTaskExecutor consumerTaskExecutor;

    /**
     * The executor for threads that invoke the listener.
     */
    private AsyncListenableTaskExecutor listenerTaskExecutor;

    public CustomConcurrentKafkaListenerContainerFactory(AsyncListenableTaskExecutor consumerTaskExecutor, AsyncListenableTaskExecutor listenerTaskExecutor) {
        this.consumerTaskExecutor = consumerTaskExecutor;
        this.listenerTaskExecutor = listenerTaskExecutor;
    }

    @Override
    protected void initializeContainer(ConcurrentMessageListenerContainer<K, V> instance) {
        super.initializeContainer(instance);
        instance.getContainerProperties().setConsumerTaskExecutor(consumerTaskExecutor);
        instance.getContainerProperties().setListenerTaskExecutor(listenerTaskExecutor);
    }
}

设置

应用自定义kafkaListenerContainerFactory，替换为本身扩展的ConcurrentKafkaListenerContainerFactory便可。

@Configuration
@AutoConfigureBefore(KafkaAutoConfiguration.class)
public class KafkaExecutorConfig {

    @Bean(name = "consumerTaskExecutor")
    public ThreadPoolTaskExecutor consumerTaskExecutor(){
        ThreadPoolTaskExecutor executor = new ThreadPoolTaskExecutor();
        executor.setCorePoolSize(Runtime.getRuntime().availableProcessors());
        executor.setMaxPoolSize(5);
        executor.setQueueCapacity(100);
        executor.setThreadNamePrefix("my-C-");
        executor.setRejectedExecutionHandler(new ThreadPoolExecutor.CallerRunsPolicy());
        executor.setWaitForTasksToCompleteOnShutdown(true);
        executor.initialize();
        return executor;
    }

    @Bean(name = "listenerTaskExecutor")
    public ThreadPoolTaskExecutor listenerTaskExecutor(){
        ThreadPoolTaskExecutor executor = new ThreadPoolTaskExecutor();
        executor.setCorePoolSize(5);
        executor.setMaxPoolSize(10);
        executor.setQueueCapacity(100);
        executor.setThreadNamePrefix("my-L-");
        executor.setRejectedExecutionHandler(new ThreadPoolExecutor.CallerRunsPolicy());
        executor.setWaitForTasksToCompleteOnShutdown(true);
        executor.initialize();
        return executor;
    }

    @Bean("kafkaListenerContainerFactory")
    public ConcurrentKafkaListenerContainerFactory<?, ?> kafkaListenerContainerFactory(
            ConcurrentKafkaListenerContainerFactoryConfigurer configurer,
            ConsumerFactory<Object, Object> kafkaConsumerFactory) {
        ConcurrentKafkaListenerContainerFactory<Object, Object> factory = new CustomConcurrentKafkaListenerContainerFactory<Object, Object>(consumerTaskExecutor(),listenerTaskExecutor());
        configurer.configure(factory, kafkaConsumerFactory);
        return factory;
    }
}

这样就大功告成了