针对分布式系统中的并发事件处理和通知处理问题，可采用阻塞/非阻塞调用和消息队列两种解决方案。其中，阻塞/非阻塞调用主要是为了解决并发处理问题，可以通过线程池实现。消息队列则用于解决通知处理问题，可采用开源框架 Kafka 或 RabbitMQ 实现。

以下是代码示例：

阻塞/非阻塞调用示例：

/**

• 线程池异步处理任务 */ ExecutorService executorService = Executors.newFixedThreadPool(10); Future future = executorService.submit(new Runnable() { @Override public void run() { //处理并发任务 } });

//阻塞式调用 future.get();

//非阻塞式调用 while (!future.isDone()) { //等待处理完成 }

消息队列示例：

//创建消息生产者 Properties props = new Properties(); props.put("bootstrap.servers", "localhost:9092"); props.put("acks", "all"); props.put("retries", 0); props.put("batch.size", 16384); props.put("linger.ms", 1); props.put("buffer.memory", 33554432); props.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer"); props.put("value.serializer", "org.apache.kafka.common.serialization.StringSerializer"); Producer producer = new KafkaProducer<>(props);

//发送消息 ProducerRecord record = new ProducerRecord<>("test", "key", "value"); producer.send(record);

//创建消息消费者 Properties props = new Properties(); props.put("bootstrap.servers", "localhost:9092"); props.put("group.id", "test"); props.put("enable.auto.commit", "true"); props.put("auto.commit.interval.ms", "1000"); props.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer"); props.put("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer"); Consumer consumer = new KafkaConsumer<>(props);

//接收消息 consumer.subscribe(Arrays.asList("test")); while (true) { ConsumerRecords records = consumer.poll(100); for (ConsumerRecord record : records) System.out.printf("offset = %d, key = %s, value = %s%n", record.offset(), record.key(), record.value()); }