Cassandra for all the Things
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At Burt we use Cassandra for a little bit of everything. We have a graph database, a tracing system, a stream processing engine and a document store that uses it for storage, and of course, we use it for time series too but with a twist. Cassandra works great for all of these use cases, but not out of the box. We've learned the hard way what not to do, and what to do instead.
Cassandra for all the Things
- 1. CASSANDRA FOR ALL THE THINGS @iconara
- 2. CASSANDRA FOR ALL THE THINGS @iconara
- 3. THEO Chief Architect at Burt @iconara
- 4. THEO Cassandra MVP and original author of the DataStax Ruby driver @iconara
- 5. CASSANDRA FOR ALL THE THINGS* @iconara
- 6. CASSANDRA FOR ALL THE THINGS* * where it makes sense @iconara
- 8. BIG TABLE partitions as sorted maps @iconara
- 9. DYNAMO availability and simple ops @iconara
- 10. LOGS AS STORAGE optimized for writes @iconara
- 12. CONVERSION TRACKING $ $ $ $ $ @iconara
- 14. ATTRIBUTION 90s 5s @iconara 30s $
- 15. visitor ID timestamp timestamp timestamp event event event
- 16. visitor ID visitor ID timestamp timestamp timestamp event event event timestamp timestamp timestamp event event event visitor ID visitor ID timestamp timestamp timestamp event event event timestamp timestamp timestamp event event event visitor ID timestamp timestamp timestamp event event event
- 18. TTL automatic windowing @iconara
- 19. ANALYTICS precomputed cubes @iconara
- 20. SELECT category, author, device_type, COUNT(*) AS pageviews, AVG(duration) AS duration FROM pageviews GROUP BY 1, 2, 3 @iconara
- 21. SELECT category, author, device_type, COUNT(*) AS pageviews, AVG(duration) AS duration FROM pageviews GROUP BY 1, 2, 3 @iconara
- 22. SELECT category, author, device_type, COUNT(*) AS pageviews, AVG(duration) AS duration FROM pageviews GROUP BY 1, 2, 3 @iconara
- 23. date + cube slice + time slice + time slice + time metrics metrics metrics
- 24. sports, Sue, tablet date + cube slice + time slice + time slice + time metrics metrics metrics category, author, device type
- 25. date + cube slice + time slice + time slice + time metrics metrics metrics {pageviews: 234, duration: 2451.45}
- 26. COUNTERS at 2M increments per second theyre not cost-effective @iconara
- 27. WIDE ROWS FAIL cardinality kills @iconara
- 28. sports, Sue, tablet date + cube slice + time slice + time slice + time metrics metrics metrics
- 30. remember when we thought this was a problem?
- 31. date + cube + shard slice + time slice + time slice + time metrics metrics metrics H(slice) mod 12
- 33. cube + slice + metric time time time value value value cube slice slice slice
- 35. cube + slice + epoch + metric time + version time + version time + version value value value cube + epoch slice slice slice time/1000
- 36. NARROW ROWS enables parallel reads @iconara
- 37. SELECT category, device_type, COUNT(*) AS pageviews, AVG(duration) AS duration FROM pageviews WHERE category = sports GROUP BY 1, 2, 3
- 38. category + device type culture + computer culture + tablet news + computer news + tablet news + mobile sports + computer sports + tablet sports + mobile
- 39. supports wildcard on device type category + device type culture + computer culture + tablet news + computer news + tablet news + mobile sports + computer sports + tablet sports + mobile device type + category computer + culture computer + news computer + sports mobile + news mobile + sports tablet + culture tablet + news tablet + sports supports wildcard on category
- 40. TRANSIENT STATE @iconara
- 41. session ID timestamp timestamp timestamp data data data shard session ID session ID session ID H(session ID) mod 360
- 42. WIDE ROWS FAIL (again) @iconara
- 43. shard 9 NFNJ0U NFNJ13 NFNJ0Y NFNJ1L NFNJ16 NFNJ0U NFNJ1C NFNJ20 NFNJ0U NFNJ2L NFNJ2S NFNJ2D NFNJ2U NFNJ1X NFNJ4C NFNJ1O NFNJ1A NFNJ29
- 44. session ID timestamp timestamp timestamp data data data shard session ID session ID session ID
- 45. session ID timestamp timestamp timestamp data data data shard + slot session ID session ID session ID
- 46. session ID timestamp timestamp timestamp data data data shard + slot session ID session ID session ID day-of-year mod 30
- 47. shard 9 slot 1 shard 9 slot 3 NFNJ6Z NFNJ73 NFNJ7B NFNJ72 NFNJ7N NFNJ74 NFNJ6Z NFNJ8C NFNJ7N NFNJ88 NFNJ83 NFNJ94 NFNJ8Z NFNJ7P NFNJA3 shard 9 slot 2 NFNJ58 NFNJ5H NFNJ5C NFNJ5E NFNJ68 NFNJ6H NFNJ68 NFNJ5M NFNJ64 NFNJ6H NFNJ6C NFNJ5U NFNJ5K NFNJ84 NFNJ7Y NFNJ62 NFNJ70 NFNJ74 NFNJ6Q
- 49. GRAPHS @iconara
- 50. TRACES @iconara
- 52. CASSANDRA FOR ALL THE THINGS @iconara