Celery meets Singleton

--- title: Celery meets Singleton tags: Slide, Python, Celery, singleton description: View the slide with "Slide Mode". slideOptions: spotlight: enabled: false allottedMinutes: 25 --- Celery meets Singleton ===   > [name=郭學聰 Hsueh-Tsung Kuo] > [time=Sun, 06 Sep 2020] [color=red] ###### CC BY-SA 4.0 ---  ## Who am I? ![fieliapm](https://www.gravatar.com/avatar/2aef78f04240a6ac9ccd473ba1cbd1e3?size=2048 =384x384) <small>Someone (who?) said: a game programmer should be able to draw cute anime character(?)</small> ----  * A programmer from game company in Taiwan * Backend (and temporary frontend) engineer, focus on common service * Usually develop something related to my work in Python, Ruby, ECMAScript, Golang, C# * ECMAScript hater since **Netscape** is dead ----  * Built CDN-aware game asset update system * Built almost entire VOEZ game server by myself only * Supported Sdorica backend development * Verify and tweak Soul of Eden backend performance ---  ## Outline ----  4. Celery 5. Singleton Task * Situations * Cases 6. Current Implementation * Principle * Local Mutex * Traditional Database * Redis & Google Cloud Memory Store ----  7. Alternative Implementation * Repository * Inspect * Task Collective Suicide * Demo 8. Conclusion 9. Reference 10. Q&A ---  ## Celery ----  ### What is Celery https://docs.celeryproject.org/en/stable/ ----  ### Structure ```graphviz digraph { compound=true rankdir=LR graph [fontname="Source Sans Pro" fontsize=20] node [fontname="Source Sans Pro" fontsize=18] edge [fontname="Source Sans Pro" fontsize=12] subgraph cluster_service { label="service" task_1 [label="task 1" shape=box] task_2 [label="task 2" shape=box] peroidic_task [label="periodic task" shape=box] } subgraph cluster_broker { label="Celery broker (call, inspect)" concentrate=true amqp [label="RabbitMQ AMQP" shape=box] } subgraph cluster_backend { label="Celery backend (result)" concentrate=true rpc [label="RabbitMQ RPC" shape=box] } subgraph cluster_worker { label="Celery worker" worker_1 [label="worker 1" shape=box] worker_2 [label="worker 2" shape=box] worker_3 [label="worker 3" shape=box] } task_1 -> amqp [color="blue"] task_2 -> amqp [color="blue"] peroidic_task -> amqp [color="blue"] amqp -> worker_1 [color="blue"] amqp -> worker_2 [color="blue"] amqp -> worker_3 [color="blue"] amqp -> worker_1 [color="pink" style="dashed" dir="both"] amqp -> worker_2 [color="pink" style="dashed" dir="both"] amqp -> worker_3 [color="pink" style="dashed" dir="both"] rpc -> task_1 [color="red"] rpc -> task_2 [color="red"] rpc -> peroidic_task [color="red"] worker_1 -> rpc [color="red"] worker_2 -> rpc [color="red"] worker_3 -> rpc [color="red"] } ``` ----  ### Usage ```python= @app.task def my_task(arg1, arg2, kwarg1='a', kwarg2='b'): ... return result result = my_task.delay(arg1, arg2, kwarg1='x', kwarg2='y') result = my_task.apply_async(args=[arg1, arg2], kwargs={'kwarg1': 'x', 'kwarg2': 'y'}, countdown=60, expires=120) result.get() ``` ---  ## Singleton Task ----  ### Situations * Only one task can be running at any given time * Launch only one worker * *Pile tasks up* * Only one task can be **queued** at any given time * Skip running task which is queued later ----  ### Cases * Garbage collect any resource * Clear blobs on S3/GCS * Schedule background updating task * Update all user data everyday ---  ## Current Implementation ----  ### Principle #1 * Sender checks existence of same task * If there is no same task queued or running * Send task to queue ----  ### Principle #2 * Worker accepts task * If any same task is already running * Skip task and quit execution * **Need at least two workers to flush out tasks** ----  ### Local Mutex * Try to lock mutex * Use mutex locking to identify if task is running ----  ### Traditional Database * Try to write semaphore into database * Check database to identify if task is running ----  ### Redis & Google Cloud Memory Store * Try to write a lock into Redis * Use SETNX * Check Redis lock to identify if task is running * Identify return value of SETNX ----  #### Redis Based Example Celery-Singleton https://github.com/steinitzu/celery-singleton ----  #### Redis Based Feature * Efficient * Responsive * No one will unlock Redis lock if worker is panic * Set lock TTL * Cannot estimate reasonable TTL when task duration is very unstable ---  ## Another Implementation ----  ### Repository # CCS ----  #### ~~CCS~~ ~~Card Captor Sakura~~ ![card_captor_sakura](https://upload.wikimedia.org/wikipedia/en/5/50/Cardcaptor_Sakura_vol1_cover.jpg) ----  #### CCS Celery-controlled singleton https://github.com/fieliapm/celery_controlled_singleton ----  ### Inspect * If any same task is already running (active) * Skip task and quit execution ----  #### Idea :bulb: ```python= i = celery_app.control.inspect(timeout=1.0) # collect response after 1.0 second i.active() # get active tasks # then find same tasks in active tasks ``` ----  #### Detail <style> code.blue { color: #337AB7 !important; } code.orange { color: #F7A004 !important; } </style> * <code class="orange">inspect.active()</code>: running tasks * <code class="blue">inspect.reserved()</code>: queued tasks * <code class="blue">inspect.scheduled()</code>: scheduled ETA tasks :warning: You cannot atomically inspect all of them ----  #### Feature * Broker/backend independent * Based on any broker/backend such as AMQP/RPC :100: * Don't need Redis lock * Don't need to argue with SRE :tada: * Inspect is slow * Affected by **timeout** parameter  * Short timeout causes inspect result missing  * Are delayed tasks really urgent?  ----  #### Race Condition # Task Collective Suicide ----  ### Task Collective Suicide ----  #### Reason * Task 1 and task 2 have same function & parameter * Worker 1 accepts task 1 * Worker 2 accepts task 2 * They started simultaneously * Worker 1 inspects and found task 2 * Worker 2 inspects and found task 1 * Worker 1 skips task 1 and quit * Worker 2 skips task 2 and quit * No worker finishes the singleton task ----  #### Solution * Absolute time_start * Since v4.2.0rc1 * Find same tasks with the earliest time_start ----  #### Trap * Multiple worker instances * No truly absolute time_start * Race hazard happens ----  ##### Reason * Current standard time is 12:00:01 * Worker 1 accepts task 1 at 12:00:03 (12:00:01) * Worker 1 inspects :arrow_right: task 1 is first task * Worker 2 accepts task 2 at 12:00:00 (12:00:02) * Worker 2 inspects :arrow_right: task 2 is first task * Because task 2 has earlier time_start * Worker 1 runs task 1 * Worker 2 runs task 2 * Two same tasks are running ----  ##### Reason (Alternative) * Worker 1 accepts task 1 * Worker 2 accepts task 2 * Worker 2 reports task 2 active to broker * Worker 2 inspects :arrow_right: task 2 is first task * Worker 1 reports task 1 active to broker (lag) * Worker 1 inspects :arrow_right: task 1 is first task * Worker 1 runs task 1 * Worker 2 runs task 2 * Two same tasks are running ----  #### Mitigate Race Condition * Delay before inspection * To ensure all same tasks listed in active list ----  ### Demo Celery-controlled singleton https://github.com/fieliapm/celery_controlled_singleton ---  ## Conclusion ----  ### Contribute! * fieliapm/celery_controlled_singleton * Better implementation * No race condition > [name=郭學聰 Hsueh-Tsung Kuo] [time=2020_09_06] [color=red] :notebook: ---  ## Reference ----  ### Link * celery * https://docs.celeryproject.org/en/stable/ * how to implement single task: * <small>https://stackoverflow.com/questions/20894771/celery-beat-limit-to-single-task-instance-at-a-time</small> * another possibility: * <small>https://stackoverflow.com/questions/20091505/celery-task-with-a-time-start-attribute-in-1970/20096342</small> * https://github.com/celery/celery/pull/3684 <small><small>https://github.com/celery/celery/blob/c0e587e94575d7be9bfdabe40c1d5dfda268e68e/celery/worker/request.py#L432</small></small> ---  ## Q&A --- <style> .reveal { background: #FFDFEF; 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