回答您的问题：
1.是的，基本上就是这样。
1.我们的解决方案是为CPU密集型任务创建一个单独的进程。

import time
from multiprocessing import Process

import pika

connection = pika.BlockingConnection(
    pika.ConnectionParameters(host='localhost'))
channel = connection.channel()

channel.exchange_declare(exchange='logs', exchange_type='fanout')
result = channel.queue_declare(queue='', exclusive=True)
queue_name = result.method.queue
channel.queue_bind(exchange='logs', queue=queue_name)

def cpu_intensive_task(ch, method, properties, body):

    def work(body):
        time.sleep(60)  # If I remember well default HB is 30 seconds
        print(" [x] %r" % body)

    p = Process(target=work, args=(body,))
    p.start()
    # Important to notice if you do p.join() You will have the same problem.

channel.basic_consume(
    queue=queue_name, on_message_callback=cpu_intensive_task, auto_ack=True)

channel.start_consuming()

我想知道这是否是这个问题的最佳解决方案，或者rabbitMQ是否是处理CPU密集型任务的最佳工具。（对于非常长的CPU密集型任务（超过30分钟），如果您发送手动ACK，您还需要处理以下问题：https://www.rabbitmq.com/consumers.html#acknowledgement-timeout)