Scaling up task processing with Celery

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Short talk I gave at Stockholm Python User Group meetup on May 7th about scaling tasks queue processing for Python applications.

Published in: Technology, Self Improvement

Scaling up task processing with Celery

  1. 1. Scaling up task processing with Celery Stockholm Python User Group – May 7th 2014
  2. 2. Hej, my name is Nicolas Grasset, and I work here at Lifesum.
  3. 3. What is Celery?
  4. 4. “Celery is an asynchronous task queue based on distributed message passing”
  5. 5. Celery runs on Python (2.5, 2.6, 2.7, 3.2, 3.3) PyPy (1.8, 1.9) and Jython (2.5, 2.7). It is maintained by Ask Solem, supported by Pivotal and released under BSD License
  6. 6. ! ! @user_required! def verify_in_app_purchase(request):! """! API to verify in-app purchase against iTunes! """! ! receipt = request.POST.get('receipt', None)! ! if not receipt:! raise Http404! ! # Warning, this takes 2sec on average! request.user.save_receipt_if_valid( receipt )! ! return Response({'thank': 'you'})! ! ! Why task queues?
  7. 7. ! ! @user_required! def verify_in_app_purchase(request):! """! API to verify in-app purchase against iTunes! """! ! receipt = request.POST.get('receipt', None)! ! if not receipt:! raise Http404! ! # Warning, this takes 2sec on average! request.user.save_receipt_if_valid( receipt )! ! return Response({'thank': 'you'})! ! ! task queues
  8. 8. Distributed? Producer Producer Producer Broker Broker Worker Worker Worker Worker Worker
  9. 9. …for High Availability and speed Flask + Celery Django + Celery Celery + Celery Redis RabbitMQ Celery Celery Celery Celery Celery
  10. 10. Celery is simple ! ! ! ! ! from celery import Celery! ! app = Celery('hello', broker='amqp://guest@localhost//')! ! @app.task(ignore_result=True)! def hello():! return 'hello world'! ! hello.delay()! ! ! ! ! !
  11. 11. 10 things I learnt on the way
  12. 12. 1. Start simple Single broker. Single queue aptitude install rabbitmq-server
  13. 13. 2. Watch for the results ! ! ! ! ! from celery import Celery! ! app = Celery('hello', broker='amqp://guest@localhost//')! ! @app.task(ignore_result=True)! def hello():! return 'hello world'! ! @app.task! def hello_memory_usage():! return 'hello world'! ! ! !
  14. 14. 3. Monitor it!
  15. 15. 4. Consume tasks faster than you produce them.
  16. 16. 5. Tweaking for concurrency ! python -m celery worker -E --time-limit=300 -c 64 -P eventlet! python -m celery worker -E --time-limit=300 -c 8 -P prefork! python -m celery worker -E --time-limit=300 --autoscale=10,3 --maxtasksperchild=10000! ! import eventlet! ! eventlet.monkey_patch()! eventlet.monkey_patch(MySQLdb=True)! !
  17. 17. 6. Scale worker/producer in pair MySQL on RDS with fail-over Python Application ~2-16 Auto-Scaling instances nginx http + celery workers Elastic Load Balancer *.lifesum.com MySQL read-replica Redis cluster for cache Sphinx SearchRabbit MQ ElasticSearch Amazon CloudFront S3 Storage Sendgrid.com Email delivery getPusher.com Socket Communication Parse.com Mobile Push Notifications iPhone apps Android apps Web users System architecture, March 2014
  18. 18. 7. Keep your tasks clean ! ! from celery.task import task! ! @task(ignore_result=True)! def will_take_some_time(list_of_users, sometimes=False):! my_favorite_utils(list_of_users, sometimes)! !
  19. 19. 8. Manage DB transactions ! from django.db import transaction! from djcelery_transactions import task! from models import Message! ! @task(ignore_result=True)! def mark_messages_as_read(user_id, day):! with transaction.commit_on_success():! Message.objects.filter(user_id=user_id, day=day).update(read=True)! ! ! @task(ignore_result=True)! def create_messages(list_of_users, day, message):! with transaction.commit_on_success():! for user_id in list_of_users:! Message.objects.create(user_id=user_id, day=day, text=message)! mark_messages_as_read.delay(user_id, day)!
  20. 20. 9. Replace your cron jobs ! from celery.schedules import crontab! ! CELERYBEAT_SCHEDULE = {! # Executes every Monday morning at 7:30 A.M! 'add-every-monday-morning': {! 'task': 'tasks.add',! 'schedule': crontab(hour=7, minute=30, day_of_week=1),! 'args': (16, 16),! },! }! ! python -m celery worker -B!
  21. 21. 10. Locks ! LOCK_EXPIRE = 60 * 5 # Lock expires in 5 minutes! ! @task(ignore_result=True)! def delete_messages(user_id):! ! lock_id = ‘lock-mark_messages_as_read-{0}’.format(user_id)! acquire_lock = lambda: cache.add(lock_id, 'true', LOCK_EXPIRE)! release_lock = lambda: cache.delete(lock_id)! ! if acquire_lock():! try:! Message.objects.filter(user_id=user_id).delete()! finally:! release_lock()! return True! ! logger.warning("Lock was not acquired!")!
  22. 22. Thanks! Reach me by email at nicolas@lifesum.com or on Twitter @fellowshipofone

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