How can I retrieve a list of tasks in a queue that are yet to be processed?
EDIT: See other answers for getting a list of tasks in the queue.
You should look here:
Celery Guide - Inspecting Workers
Basically this:
my_app = Celery(...)
# Inspect all nodes.
i = my_app.control.inspect()
# Show the items that have an ETA or are scheduled for later processing
i.scheduled()
# Show tasks that are currently active.
i.active()
# Show tasks that have been claimed by workers
i.reserved()
Depending on what you want
If you are using Celery+Django simplest way to inspect tasks using commands directly from your terminal in your virtual environment or using a full path to celery:
Doc: http://docs.celeryproject.org/en/latest/userguide/workers.html?highlight=revoke#inspecting-workers
$ celery inspect reserved
$ celery inspect active
$ celery inspect registered
$ celery inspect scheduled
Also if you are using Celery+RabbitMQ you can inspect the list of queues using the following command:
More info: https://linux.die.net/man/1/rabbitmqctl
$ sudo rabbitmqctl list_queues
if you are using rabbitMQ, use this in terminal:
sudo rabbitmqctl list_queues
it will print list of queues with number of pending tasks. for example:
Listing queues ...
0b27d8c59fba4974893ec22d478a7093 0
0e0a2da9828a48bc86fe993b210d984f 0
10#torob2.celery.pidbox 0
11926b79e30a4f0a9d95df61b6f402f7 0
15c036ad25884b82839495fb29bd6395 1
celerey_mail_worker#torob2.celery.pidbox 0
celery 166
celeryev.795ec5bb-a919-46a8-80c6-5d91d2fcf2aa 0
celeryev.faa4da32-a225-4f6c-be3b-d8814856d1b6 0
the number in right column is number of tasks in the queue. in above, celery queue has 166 pending task.
If you don't use prioritized tasks, this is actually pretty simple if you're using Redis. To get the task counts:
redis-cli -h HOST -p PORT -n DATABASE_NUMBER llen QUEUE_NAME
But, prioritized tasks use a different key in redis, so the full picture is slightly more complicated. The full picture is that you need to query redis for every priority of task. In python (and from the Flower project), this looks like:
PRIORITY_SEP = '\x06\x16'
DEFAULT_PRIORITY_STEPS = [0, 3, 6, 9]
def make_queue_name_for_pri(queue, pri):
"""Make a queue name for redis
Celery uses PRIORITY_SEP to separate different priorities of tasks into
different queues in Redis. Each queue-priority combination becomes a key in
redis with names like:
- batch1\x06\x163 <-- P3 queue named batch1
There's more information about this in Github, but it doesn't look like it
will change any time soon:
- https://github.com/celery/kombu/issues/422
In that ticket the code below, from the Flower project, is referenced:
- https://github.com/mher/flower/blob/master/flower/utils/broker.py#L135
:param queue: The name of the queue to make a name for.
:param pri: The priority to make a name with.
:return: A name for the queue-priority pair.
"""
if pri not in DEFAULT_PRIORITY_STEPS:
raise ValueError('Priority not in priority steps')
return '{0}{1}{2}'.format(*((queue, PRIORITY_SEP, pri) if pri else
(queue, '', '')))
def get_queue_length(queue_name='celery'):
"""Get the number of tasks in a celery queue.
:param queue_name: The name of the queue you want to inspect.
:return: the number of items in the queue.
"""
priority_names = [make_queue_name_for_pri(queue_name, pri) for pri in
DEFAULT_PRIORITY_STEPS]
r = redis.StrictRedis(
host=settings.REDIS_HOST,
port=settings.REDIS_PORT,
db=settings.REDIS_DATABASES['CELERY'],
)
return sum([r.llen(x) for x in priority_names])
If you want to get an actual task, you can use something like:
redis-cli -h HOST -p PORT -n DATABASE_NUMBER lrange QUEUE_NAME 0 -1
From there you'll have to deserialize the returned list. In my case I was able to accomplish this with something like:
r = redis.StrictRedis(
host=settings.REDIS_HOST,
port=settings.REDIS_PORT,
db=settings.REDIS_DATABASES['CELERY'],
)
l = r.lrange('celery', 0, -1)
pickle.loads(base64.decodestring(json.loads(l[0])['body']))
Just be warned that deserialization can take a moment, and you'll need to adjust the commands above to work with various priorities.
To retrieve tasks from backend, use this
from amqplib import client_0_8 as amqp
conn = amqp.Connection(host="localhost:5672 ", userid="guest",
password="guest", virtual_host="/", insist=False)
chan = conn.channel()
name, jobs, consumers = chan.queue_declare(queue="queue_name", passive=True)
A copy-paste solution for Redis with json serialization:
def get_celery_queue_items(queue_name):
import base64
import json
# Get a configured instance of a celery app:
from yourproject.celery import app as celery_app
with celery_app.pool.acquire(block=True) as conn:
tasks = conn.default_channel.client.lrange(queue_name, 0, -1)
decoded_tasks = []
for task in tasks:
j = json.loads(task)
body = json.loads(base64.b64decode(j['body']))
decoded_tasks.append(body)
return decoded_tasks
It works with Django. Just don't forget to change yourproject.celery.
This worked for me in my application:
def get_celery_queue_active_jobs(queue_name):
connection = <CELERY_APP_INSTANCE>.connection()
try:
channel = connection.channel()
name, jobs, consumers = channel.queue_declare(queue=queue_name, passive=True)
active_jobs = []
def dump_message(message):
active_jobs.append(message.properties['application_headers']['task'])
channel.basic_consume(queue=queue_name, callback=dump_message)
for job in range(jobs):
connection.drain_events()
return active_jobs
finally:
connection.close()
active_jobs will be a list of strings that correspond to tasks in the queue.
Don't forget to swap out CELERY_APP_INSTANCE with your own.
Thanks to #ashish for pointing me in the right direction with his answer here: https://stackoverflow.com/a/19465670/9843399
The celery inspect module appears to only be aware of the tasks from the workers perspective. If you want to view the messages that are in the queue (yet to be pulled by the workers) I suggest to use pyrabbit, which can interface with the rabbitmq http api to retrieve all kinds of information from the queue.
An example can be found here:
Retrieve queue length with Celery (RabbitMQ, Django)
I think the only way to get the tasks that are waiting is to keep a list of tasks you started and let the task remove itself from the list when it's started.
With rabbitmqctl and list_queues you can get an overview of how many tasks are waiting, but not the tasks itself: http://www.rabbitmq.com/man/rabbitmqctl.1.man.html
If what you want includes the task being processed, but are not finished yet, you can keep a list of you tasks and check their states:
from tasks import add
result = add.delay(4, 4)
result.ready() # True if finished
Or you let Celery store the results with CELERY_RESULT_BACKEND and check which of your tasks are not in there.
As far as I know Celery does not give API for examining tasks that are waiting in the queue. This is broker-specific. If you use Redis as a broker for an example, then examining tasks that are waiting in the celery (default) queue is as simple as:
connect to the broker
list items in the celery list (LRANGE command for an example)
Keep in mind that these are tasks WAITING to be picked by available workers. Your cluster may have some tasks running - those will not be in this list as they have already been picked.
The process of retrieving tasks in particular queue is broker-specific.
I've come to the conclusion the best way to get the number of jobs on a queue is to use rabbitmqctl as has been suggested several times here. To allow any chosen user to run the command with sudo I followed the instructions here (I did skip editing the profile part as I don't mind typing in sudo before the command.)
I also grabbed jamesc's grep and cut snippet and wrapped it up in subprocess calls.
from subprocess import Popen, PIPE
p1 = Popen(["sudo", "rabbitmqctl", "list_queues", "-p", "[name of your virtula host"], stdout=PIPE)
p2 = Popen(["grep", "-e", "^celery\s"], stdin=p1.stdout, stdout=PIPE)
p3 = Popen(["cut", "-f2"], stdin=p2.stdout, stdout=PIPE)
p1.stdout.close()
p2.stdout.close()
print("number of jobs on queue: %i" % int(p3.communicate()[0]))
If you control the code of the tasks then you can work around the problem by letting a task trigger a trivial retry the first time it executes, then checking inspect().reserved(). The retry registers the task with the result backend, and celery can see that. The task must accept self or context as first parameter so we can access the retry count.
#task(bind=True)
def mytask(self):
if self.request.retries == 0:
raise self.retry(exc=MyTrivialError(), countdown=1)
...
This solution is broker agnostic, ie. you don't have to worry about whether you are using RabbitMQ or Redis to store the tasks.
EDIT: after testing I've found this to be only a partial solution. The size of reserved is limited to the prefetch setting for the worker.
from celery.task.control import inspect
def key_in_list(k, l):
return bool([True for i in l if k in i.values()])
def check_task(task_id):
task_value_dict = inspect().active().values()
for task_list in task_value_dict:
if self.key_in_list(task_id, task_list):
return True
return False
With subprocess.run:
import subprocess
import re
active_process_txt = subprocess.run(['celery', '-A', 'my_proj', 'inspect', 'active'],
stdout=subprocess.PIPE).stdout.decode('utf-8')
return len(re.findall(r'worker_pid', active_process_txt))
Be careful to change my_proj with your_proj
To get the number of tasks on a queue you can use the flower library, here is a simplified example:
from flower.utils.broker import Broker
from django.conf import settings
def get_queue_length(queue):
broker = Broker(settings.CELERY_BROKER_URL)
queues_result = broker.queues([queue])
return queues_result.result()[0]['messages']
I have Started my job using jobLauncher.run(processJob,jobParameters); and when i try stop job using another request jobOperator.stop(jobExecution.getId()); then get exeption :
org.springframework.batch.core.launch.JobExecutionNotRunningException:
JobExecution must be running so that it can be stopped
Set<JobExecution> jobExecutionsSet= jobExplorer.findRunningJobExecutions("processJob");
for (JobExecution jobExecution:jobExecutionsSet) {
System.err.println("job status : "+ jobExecution.getStatus());
if (jobExecution.getStatus()== BatchStatus.STARTED|| jobExecution.getStatus()== BatchStatus.STARTING || jobExecution.getStatus()== BatchStatus.STOPPING){
jobOperator.stop(jobExecution.getId());
System.out.println("###########Stopped#########");
}
}
when print job status always get job status : STOPPING but batch job is running
its web app, first upload some CSV file and start some operation using spring batch and during this execution if user need stop then stop request from another controller method come and try to stop running job
Please help me for stop running job
If you stop a job while it is running (typically in a STARTED state), you should not get this exception. If you have this exception, it means you have stopped your job while it is currently stopping (that is what the STOPPING status means).
jobExplorer.findRunningJobExecutions returns only running executions, so if in the next line right after this one you have a job in STOPPING status, this means the status changed right after calling jobExplorer.findRunningJobExecutions. You need to be aware that this is possible and your controller should handle this case.
When you tell spring batch to stop a job it goes into STOPPING mode. What this means is it will attempt to complete the unit of work chunk it is currently processing but then stop working. Likely what's happening is you are working on a long running task that is not finishing a unit of work (is it hung?) so it can't move from STOPPING to STOPPED.
Doing it twice rightly leads to an Exception because your job is already STOPPING by the time you did it the first time.
I'm using Celery 4.3.0 to create a group of tasks to run. When I do this the tasks themselves all execute successfully but the GroupResult completed count is always 0.
I'm using rabbitmq broker and have tried redis result backend and db result backend, it acts the same.
#shared_task(
autoretry_for=(Exception,), retry_backoff=
ignore_result=False, retry_kwargs={'max_retries': 3},
)
def some_task(*args, **kwargs):
logger.info('some task')
def run_tasks():
tasks = [some_task.s(), some_task.s()]
result = group(*tasks).apply_async()
while True:
print(result.completed_count())
You can update celery to 4.4.1. I had the same problem before updating.
How spring batch admin is stopping a running job from the UI .
On the spring batch admin's online documentation i have read the following lines .
"A job that is executing can be stopped by the user (whether or not it
is launchable). The stop signal is sent via the database and once
detected by Spring Batch in whatever process is running the job, the
job is stopped (status moves from STOPPING to STOPPED) and no further
processing takes place."
Does that mean Spring batch admin UI is directly changing the status of job inside the spring batch table ?
UPDATE: I tried executing the below query on the running job .
update batch_job_execution set status="STOPPED" where job_ins
tance_id=19;
The above query is getting updated in the DB but spring batch is not bale to stop the running job.
If anybody has tried this please do share the logic here .
You're confused between Batch Status vs. Exit Status.
What are you doing with that SQL is changed the STATUS to STOPPED
When a job is running you can stop the job from the code. In each step iteration, check their status and if STOPPING its set, then send the step to stop ongoing.
Anyway, what you doing is not elegant. The correct way is explained in Common Batch Patterns -> 11.2 Stopping a Job Manually for Business Reasons
public class FooProcessor implements ItemProcessor<FooIn,FooOut>{
public FooOut process(FooIn foo) throws Exception {
if (sendToStop(item)) {
throw new MyStopException("I need to Stop: " + item);
}
//do my stuff
return new FooOut(foo);
}
}
Another simple way to stop chunk step is return null in the reader. This tells us that no more elements to iterate the reader
public T read() throws Exception {
T item = delegate.read();
if (ifNeedStop(item)) {
return null; // end the step here
}
return item;
}
I investigated the spring batch code.
It seems they update both the version and status of the BATCH_JOB_EXECUTION.
This works for me:
update batch_job_execution set status="STOPPED", version=version+1 where job_instance_id=19;
If you look into the jars of spring batch admin, you can see that in AbstractStep.java(spring-batch admin class) it checks for the status of the Step and Job from Database .
Based on this status it validates step before running it .
This works well for all cases except in chunk, since next step is called after large processing . If you want to implement in it, you can implement your own listener to check status (but it will increase DB hits) .