从多个队列中消费的 Celery Worker 如何决定先消费哪一个？

Question

我正在使用 Celery 执行异步后台任务，以 Redis 作为后端。我对 Celery 工人在以下情况下的行为感兴趣：

我正在使用

celeryd

将工作程序作为守护进程运行。该工作人员已被分配两个队列以通过

-Q

选项进行消费：

celeryd -E -Q queue1,queue2

worker 如何决定从哪里获取下一个任务来消费？ 它是否随机消费来自

queue1

或

queue2

的任务？它是否会优先从

queue1

获取，因为它位于传递给

-Q

的参数列表中的第一个？

Answer 1

根据我的测试，它处理多个队列循环方式。

如果我使用这个测试代码：

from celery import task
import time


@task
def my_task(item_id):
    time.sleep(0.5)
    print('Processing item "%s"...' % item_id)


def add_items_to_queue(queue_name, items_count):
    for i in xrange(0, items_count):
        my_task.apply_async(('%s-%d' % (queue_name, i),), queue=queue_name)


add_items_to_queue('queue1', 10)
add_items_to_queue('queue2', 10)
add_items_to_queue('queue3', 5)

并启动队列（使用 django-celery）：

`manage.py celery worker -Q queue1,queue2,queue3`

它输出：

Processing item "queue1-0"...
Processing item "queue3-0"...
Processing item "queue2-0"...
Processing item "queue1-1"...
Processing item "queue3-1"...
Processing item "queue2-1"...
Processing item "queue1-2"...
Processing item "queue3-2"...
Processing item "queue2-2"...
Processing item "queue1-3"...
Processing item "queue3-3"...
Processing item "queue2-3"...
Processing item "queue1-4"...
Processing item "queue3-4"...
Processing item "queue2-4"...
Processing item "queue1-5"...
Processing item "queue2-5"...
Processing item "queue1-6"...
Processing item "queue2-6"...
Processing item "queue1-7"...
Processing item "queue2-7"...
Processing item "queue1-8"...
Processing item "queue2-8"...
Processing item "queue1-9"...
Processing item "queue2-9"...

因此，它会在继续处理下一个队列 1 项目之前从每个队列中提取一个项目，即使所有队列 1 任务都在队列 2 和 3 任务之前发布。

注意： 正如 @WarLord 指出的，只有当

CELERYD_PREFETCH_MULTIPLIER

设置为 1 时，此行为才会起作用。如果它大于 1，则意味着将从队列中分批获取项目。因此，如果您有 4 个进程，且 PREFETCH_MULTIPLIER 设置为 4，则意味着将立即从队列中提取 16 个项目，因此您不会获得如上所述的确切输出，但它仍然会大致跟随循环-罗宾。

Answer 2

注意： 这个答案已被弃用：最新版本的 Celery 的工作方式与 2013 年的非常不同......

消耗多个队列的工作线程也消耗任务，跨多个队列也维持 FIFO 顺序。

示例：

队列1：（t1，t2，t5，t7）

队列2：（t0，t3，t4，t6）

假设0-7代表发布任务的顺序

消费顺序为 t0, t1, t2, t3, t4, t5, t6, t7

Answer 3

使用指向rabbitmq服务器的pyamqp代理库，任务以循环方式处理。请参阅下面的证明。

看来处理的订单任务是由代理

库决定的，而不是实际的后端（rabbitmq vs redis不是问题）。

软件版本：

$ pip freeze | egrep "celery|kombu|amqp"
amqp==2.5.2
celery==4.4.2
kombu==4.6.8

from time import sleep

@app.task
def sleepy(name):
    print(f"Processing: {name}")
    sleep(0.5)

然后在另一个 shell 中，将任务排队：

from time import sleep

def queue_them():
    for x in range(50):
        sleepy.apply_async(args=(f"Q1-T{x}",), queue="Q1")
    sleep(0.1)
    for x in range(20):
        sleepy.apply_async(args=(f"Q2-T{x}",), queue="Q2")
    sleep(0.1)
    sleepy.apply_async(args=("Q3-T0",), queue="Q3")
    for x in range(30):
        sleepy.apply_async(args=(f"Q2MOAR-T{x}",), queue="Q2")

# setup - get celery to setup the queues and exchanges
sleepy.apply_async(args=("nothing",), queue="Q1")
sleepy.apply_async(args=("nothing",), queue="Q2")
sleepy.apply_async(args=("nothing",), queue="Q3")

# run the test
queue_them()

在另一个 shell 中，运行 celery：

$ celery worker -A myapp.celery --pool=prefork --concurrency=2 -Ofair --queues=Q1,Q3,Q2

[2020-05-05 21:59:11,547] WARNING [celery.redirected:235] Processing: Q1-T1
[2020-05-05 21:59:11,547] WARNING [celery.redirected:235] Processing: Q1-T0
[2020-05-05 21:59:12,052] WARNING [celery.redirected:235] Processing: Q1-T2
[2020-05-05 21:59:12,053] WARNING [celery.redirected:235] Processing: Q1-T3
[2020-05-05 21:59:12,556] WARNING [celery.redirected:235] Processing: Q1-T5
[2020-05-05 21:59:12,556] WARNING [celery.redirected:235] Processing: Q1-T4
[2020-05-05 21:59:13,062] WARNING [celery.redirected:235] Processing: Q1-T6
[2020-05-05 21:59:13,063] WARNING [celery.redirected:235] Processing: Q1-T7
[2020-05-05 21:59:13,565] WARNING [celery.redirected:235] Processing: Q1-T9
[2020-05-05 21:59:13,565] WARNING [celery.redirected:235] Processing: Q1-T8
[2020-05-05 21:59:14,069] WARNING [celery.redirected:235] Processing: Q1-T10
[2020-05-05 21:59:14,069] WARNING [celery.redirected:235] Processing: Q3-T0
[2020-05-05 21:59:14,571] WARNING [celery.redirected:235] Processing: Q2-T0
[2020-05-05 21:59:14,572] WARNING [celery.redirected:235] Processing: Q2-T1
[2020-05-05 21:59:15,078] WARNING [celery.redirected:235] Processing: Q1-T11
[2020-05-05 21:59:15,078] WARNING [celery.redirected:235] Processing: Q2-T2
[2020-05-05 21:59:15,581] WARNING [celery.redirected:235] Processing: Q2-T3
[2020-05-05 21:59:15,581] WARNING [celery.redirected:235] Processing: Q1-T12
[2020-05-05 21:59:16,084] WARNING [celery.redirected:235] Processing: Q1-T13
[2020-05-05 21:59:16,084] WARNING [celery.redirected:235] Processing: Q2-T4
[2020-05-05 21:59:16,586] WARNING [celery.redirected:235] Processing: Q1-T14
[2020-05-05 21:59:16,586] WARNING [celery.redirected:235] Processing: Q2-T5
[2020-05-05 21:59:17,089] WARNING [celery.redirected:235] Processing: Q1-T15
[2020-05-05 21:59:17,089] WARNING [celery.redirected:235] Processing: Q2-T6
[2020-05-05 21:59:17,591] WARNING [celery.redirected:235] Processing: Q1-T16
[2020-05-05 21:59:17,592] WARNING [celery.redirected:235] Processing: Q2-T7
[2020-05-05 21:59:18,094] WARNING [celery.redirected:235] Processing: Q1-T17
[2020-05-05 21:59:18,094] WARNING [celery.redirected:235] Processing: Q2-T8
[2020-05-05 21:59:18,597] WARNING [celery.redirected:235] Processing: Q1-T18
[2020-05-05 21:59:18,597] WARNING [celery.redirected:235] Processing: Q2-T9
[2020-05-05 21:59:19,102] WARNING [celery.redirected:235] Processing: Q1-T19
[2020-05-05 21:59:19,102] WARNING [celery.redirected:235] Processing: Q1-T20
[2020-05-05 21:59:19,607] WARNING [celery.redirected:235] Processing: Q1-T21
[2020-05-05 21:59:19,607] WARNING [celery.redirected:235] Processing: Q1-T22
[2020-05-05 21:59:20,110] WARNING [celery.redirected:235] Processing: Q1-T23
[2020-05-05 21:59:20,110] WARNING [celery.redirected:235] Processing: Q2-T10
[2020-05-05 21:59:20,614] WARNING [celery.redirected:235] Processing: Q1-T24
[2020-05-05 21:59:20,614] WARNING [celery.redirected:235] Processing: Q2-T11
[2020-05-05 21:59:21,118] WARNING [celery.redirected:235] Processing: Q1-T25
[2020-05-05 21:59:21,118] WARNING [celery.redirected:235] Processing: Q1-T26
[2020-05-05 21:59:21,622] WARNING [celery.redirected:235] Processing: Q2-T12
[2020-05-05 21:59:21,622] WARNING [celery.redirected:235] Processing: Q1-T27
[2020-05-05 21:59:22,124] WARNING [celery.redirected:235] Processing: Q1-T28
[2020-05-05 21:59:22,124] WARNING [celery.redirected:235] Processing: Q2-T13
[2020-05-05 21:59:22,627] WARNING [celery.redirected:235] Processing: Q2-T14
[2020-05-05 21:59:22,627] WARNING [celery.redirected:235] Processing: Q1-T29
[2020-05-05 21:59:23,129] WARNING [celery.redirected:235] Processing: Q1-T31
[2020-05-05 21:59:23,129] WARNING [celery.redirected:235] Processing: Q1-T30
[2020-05-05 21:59:23,631] WARNING [celery.redirected:235] Processing: Q2-T15
[2020-05-05 21:59:23,632] WARNING [celery.redirected:235] Processing: Q1-T32
[2020-05-05 21:59:24,134] WARNING [celery.redirected:235] Processing: Q1-T33
[2020-05-05 21:59:24,134] WARNING [celery.redirected:235] Processing: Q2-T16
[2020-05-05 21:59:24,636] WARNING [celery.redirected:235] Processing: Q2-T17
[2020-05-05 21:59:24,636] WARNING [celery.redirected:235] Processing: Q2-T18
[2020-05-05 21:59:25,138] WARNING [celery.redirected:235] Processing: Q2-T19
[2020-05-05 21:59:25,139] WARNING [celery.redirected:235] Processing: Q1-T34
[2020-05-05 21:59:25,641] WARNING [celery.redirected:235] Processing: Q1-T35
[2020-05-05 21:59:25,642] WARNING [celery.redirected:235] Processing: Q2MOAR-T0
[2020-05-05 21:59:26,144] WARNING [celery.redirected:235] Processing: Q1-T36
[2020-05-05 21:59:26,144] WARNING [celery.redirected:235] Processing: Q1-T37
[2020-05-05 21:59:26,649] WARNING [celery.redirected:235] Processing: Q2MOAR-T1
[2020-05-05 21:59:26,649] WARNING [celery.redirected:235] Processing: Q1-T38
[2020-05-05 21:59:27,153] WARNING [celery.redirected:235] Processing: Q2MOAR-T2
[2020-05-05 21:59:27,154] WARNING [celery.redirected:235] Processing: Q1-T39
[2020-05-05 21:59:27,656] WARNING [celery.redirected:235] Processing: Q2MOAR-T3
[2020-05-05 21:59:27,656] WARNING [celery.redirected:235] Processing: Q2MOAR-T4
[2020-05-05 21:59:28,159] WARNING [celery.redirected:235] Processing: Q2MOAR-T5
[2020-05-05 21:59:28,160] WARNING [celery.redirected:235] Processing: Q1-T40
[2020-05-05 21:59:28,664] WARNING [celery.redirected:235] Processing: Q2MOAR-T6
[2020-05-05 21:59:28,664] WARNING [celery.redirected:235] Processing: Q1-T41
[2020-05-05 21:59:29,167] WARNING [celery.redirected:235] Processing: Q2MOAR-T7
[2020-05-05 21:59:29,167] WARNING [celery.redirected:235] Processing: Q1-T42

当 celery 以 1 并发运行时，结果类似：

[2020-05-05 22:01:33,879] WARNING [celery.redirected:235] Processing: Q1-T0
[2020-05-05 22:01:34,385] WARNING [celery.redirected:235] Processing: Q1-T1
[2020-05-05 22:01:34,888] WARNING [celery.redirected:235] Processing: Q1-T2
[2020-05-05 22:01:35,391] WARNING [celery.redirected:235] Processing: Q1-T3
[2020-05-05 22:01:35,894] WARNING [celery.redirected:235] Processing: Q1-T4
[2020-05-05 22:01:36,397] WARNING [celery.redirected:235] Processing: Q1-T5
[2020-05-05 22:01:36,899] WARNING [celery.redirected:235] Processing: Q3-T0
[2020-05-05 22:01:37,404] WARNING [celery.redirected:235] Processing: Q2-T0
[2020-05-05 22:01:37,907] WARNING [celery.redirected:235] Processing: Q2-T1
[2020-05-05 22:01:38,411] WARNING [celery.redirected:235] Processing: Q1-T6
[2020-05-05 22:01:38,913] WARNING [celery.redirected:235] Processing: Q2-T2
[2020-05-05 22:01:39,417] WARNING [celery.redirected:235] Processing: Q2-T3
[2020-05-05 22:01:39,919] WARNING [celery.redirected:235] Processing: Q2-T4
[2020-05-05 22:01:40,422] WARNING [celery.redirected:235] Processing: Q1-T7
[2020-05-05 22:01:40,925] WARNING [celery.redirected:235] Processing: Q2-T5
[2020-05-05 22:01:41,429] WARNING [celery.redirected:235] Processing: Q1-T8

Answer 4

从 Celery 5.3 开始，使用 Redis 传输时，队列优先级

在某种程度上是可配置的。

首先可以通过更改

队列顺序策略来调整，这是Redis特定的代理传输选项。

它的默认值是

round_robin

，旨在为每个队列提供平等的消费机会。另一个可用值是 

priority

。根据

文档，它将：

按原始顺序从队列中消费，这样如果第一个队列始终包含消息，则列表中的其余队列将永远不会被消费。

更新配置后：

celery_app.conf.update(broker_transport_options={"queue_order_strategy": "priority"}) 第二步有必要以正确的队列顺序启动工作线程，其中应首先列出优先级较高的队列。

celery worker -Q higher_priority_queue,other_queue 据我了解，当高优先级队列中有新任务时，此设置不会停止低优先级队列中当前正在运行的任务。它将等待它完成。但随后它会再次检查优先级较高的队列。如果它包含一个新任务，它将运行它

不管其他较低优先级队列中是否有更多任务。