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Caching Up and Down the Stack
- 1. Caching Up and Down the Stack 1 James Meickle Developer evangelist, AppNeta @jmeickle Django Boston Meetup Group March 26, 2014
- 3. 3 4 WHAT IS CACHING? Uncached Cached Client Data Source Data Source Client Cache Intermediary
- 4. 4 4 WHAT IS CACHING? Uncached Cached Client Data Source Data Source Client Cache Intermediary Fast ! Slow...
- 5. 5 • Images • CSS • JavaScript • HTML documents • DNS 4 WHAT GETS CACHED BY CLIENTS?
- 6. 6 • HTML documents • HTML fragments • Operations on data • Database queries • Expensive objects 4 WHAT GETS CACHED BY APPS?
- 7. 7 • Compiled source • Packages • Disk access • Memory access • CPU instructions 4 WHAT GETS CACHED BY SERVERS?
- 8. 8 • Client-side assets • Full pages 4 CACHING IN DJANGO: FRONTEND
- 9. 9 4 OUR SITES appneta.com (static site via Jekyll)
- 10. 10 4 OUR SITES internal.tracelytics.com (dynamic single page Pylons app)
- 12. 12 • Use HTTP caches! • CDN • Intermediate proxies • Browser • Set policy with cache headers • Cache-Control • Expires 4 CLIENT-SIDE ASSETS
- 13. 13 4 CLIENT-SIDE ASSETS /tl-layouts_base-compiled-757f5eec3603f60850acfdb86e6701cf104f80ae.css Request Method: GET Status Code: 304 Not Modified Cache-Control: max-age=315360000 Connection: keep-alive Date: Mon, 18 Feb 2013 22:46:12 GMT Expires: Thu, 31 Dec 2037 23:55:55 GMT Last-Modified: Tue, 12 Feb 2013 21:10:20 GMT Server: nginx/0.8.54
- 16. 16 • Full pages • Partial pages • Objects • Queries 4 CACHING IN DJANGO: BACKEND
- 17. 17 4 WE’RE STILL TALKING ABOUT PAGES? Client-side assets Pages
- 18. 18 4 FULL-PAGE HTTP CACHING Client Varnish Do HTTP caching, but with your rules. No internet standards necessary! Webserver
- 19. 19 • Why do it server-side? • Invalidation • Amount cached • Changing cache policies 4 FULL-PAGE HTTP CACHING
- 20. 20 4 FULL-PAGE HTTP CACHING (IN DJANGO)
- 21. 21 • Full pages • Partial pages • Objects • Queries 4 CACHING IN DJANGO: BACKEND
- 29. 29 • Full pages • Partial pages • Objects • Queries 4 CACHING IN DJANGO: BACKEND
- 30. 30 4 OBJECT CACHING def get_item_by_id(key): # Look up the item in our database return session.query(User) .filter_by(id=key) .first()
- 31. 31 4 OBJECT CACHING def get_item_by_id(key): # Check in cache val = mc.get(key) # If exists, return it if val: return val # If not, get the val, store it in the cache val = return session.query(User) .filter_by(id=key) .first() mc.set(key, val) return val
- 32. 32 4 OBJECT CACHING @decorator def cache(expensive_func, key): # Check in cache val = mc.get(key) # If exists, return it if val: return val # If not, get the val, store it in the cache val = expensive_func(key) mc.set(key, val) return val
- 33. 33 4 OBJECT CACHING @cache def get_item_by_id(key): # Look up the item in our database return session.query(User) .filter_by(id=key) .first()
- 34. 34 4 OBJECT CACHING (IN DJANGO)
- 35. 35 • Full pages • Partial pages • Objects • Queries 4 CACHING IN DJANGO: BACKEND
- 36. 36 4 QUERY CACHING Cached Table Data DB client Query Cache SQL server Retrieve results from memory… …or from memcached… …or cache in the DB itself!
- 37. 37 4 QUERY CACHING mysql> select SQL_CACHE count(*) from traces; +----------+ | count(*) | +----------+ | 3135623 | +----------+ 1 row in set (0.56 sec) mysql> select SQL_CACHE count(*) from traces; +----------+ | count(*) | +----------+ | 3135623 | +----------+ 1 row in set (0.00 sec)
- 38. 38 4 QUERY CACHING (IN DJANGO)
- 39. 39 4 QUERY CACHING (IN TRACEVIEW) Cassandra in TraceView: Retrieving data from data warehouse
- 40. 40 4 QUERY CACHING (IN TRACEVIEW) Memcache in TraceView: 97%ile is 50ms!
- 41. 41 • Invalidation • Fragmentation • Stampedes • Complexity 4 WHAT CAN GO WRONG?
- 45. 45 4 INVALIDATION Do you know what you’re storing in this call?
- 47. 47 4 FRAGMENTATION “In the beginning there was NCSA Mosaic, and Mosaic called itself NCSA_Mosaic/2.0 (Windows 3.1), and Mosaic displayed pictures along with text, and there was much rejoicing.” History of the browser user-agent string
- 48. 48 • On a cache miss extra work is done • The result is stored in the cache • What if multiple simultaneous misses? • Every node tries to do the same work at the same time and your 4 STAMPEDES
- 49. 49 • What caching scheme? • How many extra servers? • What happens if they fail? • What will you do to debug it? 4 COMPLEXITY
- 50. 50 • The ‘how’ of caching: • What are you caching? • Where are you caching it? • How bad is a cache miss? • How and when are you invalidating? 4 TAKEAWAYS
- 51. 51 • The ‘why’ of caching: • Did it actually get faster? • Is speed worth extra complexity? • Don’t guess – measure! • Always use real-world conditions. 4 TAKEAWAYS
- 53. 53 • Django documentation on caching: https://docs.djangoproject.com/en/dev/topics/cache/ • Varnish caching, via Disqus: http://blog.disqus.com/post/62187806135/scaling-django-to-8- billion-page-views • Django cache option comparisons: http://codysoyland.com/2010/jan/17/evaluating-django-caching- options/ • More Django-specific tips: http://www.slideshare.net/csky/where- django-caching-bust-at-the-seams • Guide to cache-related HTTP headers: http://www.mobify.com/blog/beginners-guide-to-http-cache- headers/ 4 RESOURCES
- 54. 54 TraceView Stop by later tonight to hear more about AppNeta or TraceView (make sure to get a sticker!) April 1: Come drink on our tab after the Boston Python Meetup April 11: PyCon! Swing by our booth (214) for an awesome shirt Or, just try us out: THANK YOU! http://www.appneta.com/products/traceview/
Notes de l'éditeur
- Caches that exist at the client or CDN level
- Caches that exist within a running application’s code
- Caches that exist at the programming language or infrastructure level