We Hear You Like Papers: Eventual Consistency

Given at Women Who Code Sydney IT meetup

Resources: https://github.com/CaitieM20/Talks/tree/master/SoWeHearYouLikePapers

Transcript

1. Papers We hear you like
2. @Caitie Caitie 
 McCaffrey
3. Distributed Systems
4. Service Service Service We Are All Building Distributed Systems
5. Twitter Services
7. academic Papers
8. Eventual Consistency
9. 1983 1995 Thinking Consistency Detection of Mutual Inconsistency in Distributed Systems Managing Update Conflicts in Bayou, a Weakly Connected Replicated Storage System Brewer's conjecture & the feasibility of consistent, available, partition-tolerant web services 2002
10. 2015 2011 Conflict-free replicated Data Types Feral Concurrency Control: An Empirical Investigation of Modern Application Integrity Thinking Consistency
11. Service Service Service Applications Before
12. Service Service Service Applications Before
13. ApplicationsNow Service Service Service
15. High availability
16. High availability “In some environments it is desirable or necessary to permit users to continue modifying resources such as files when the network is partitioned”
17. Origin Points & Version Vectors
18. Version Vectors “A Version Vector for a file f is a sequence of n pairs, where n is the number of sites at which f is stored … the ith vector entry counts the number Vi of updates to f made at site Si” <A:9, B:7, C:22, D:3>
19. Compatible Version Vectors <A:1, B:2, C:4, D:3> <A:0, B:2, C:2, D:3>
20. <A:1, B:2, C:4, D:3> <A:1, B:2, C:3, D:4> Incompatible Version Vectors
21. ABCD Partition Graph <A:0, B:0, C:0, D:0>
22. ABCD AB CD Partition Graph <A:0, B:0, C:0, D:0> <A:0, B:0, C:0, D:0> <A:0, B:0, C:0, D:0>
23. ABCD AB CD Partition Graph <A:0, B:0, C:0, D:0> <A:0, B:0, C:0, D:0> <A:1, B:0, C:0, D:0>
24. ABCD AB CD D BC A Partition Graph T2 <A:0, B:0, C:0, D:0> <A:0, B:0, C:0, D:0> <A:0, B:0, C:0, D:0> <A:1, B:0, C:0, D:0> <A:1, B:0, C:0, D:0>
25. ABCD AB CD D BC A Partition Graph T2 <A:0, B:0, C:0, D:0> <A:0, B:0, C:0, D:0> <A:0, B:0, C:0, D:0> <A:1, B:0, C:0, D:0> <A:1, B:0, C:0, D:0> No Conflict!
26. ABCD AB CD D BC A Partition Graph T2 <A:0, B:0, C:0, D:0> <A:0, B:0, C:0, D:0> <A:0, B:0, C:0, D:0> <A:1, B:0, C:0, D:0> <A:1, B:0, C:0, D:0> <A:1, B:0, C:0, D:0>
27. ABCD AB CD D BC A Partition Graph T2 <A:0, B:0, C:0, D:0> <A:0, B:0, C:0, D:0> <A:0, B:0, C:0, D:0> <A:1, B:0, C:0, D:0> <A:2, B:0, C:0, D:0> <A:1, B:0, C:1, D:0>
28. ABCD AB CD D BC A BCD Partition Graph T2 <A:0, B:0, C:0, D:0> <A:0, B:0, C:0, D:0> <A:0, B:0, C:0, D:0> <A:1, B:0, C:0, D:0> <A:2, B:0, C:0, D:0> <A:1, B:0, C:1, D:0>
29. ABCD AB CD D BC A BCD Partition Graph T2 <A:0, B:0, C:0, D:0> <A:0, B:0, C:0, D:0> <A:0, B:0, C:0, D:0> <A:1, B:0, C:0, D:0> <A:2, B:0, C:0, D:0> <A:1, B:0, C:1, D:0> No Conflict!
30. ABCD AB CD D BC A BCD Partition Graph T2 <A:0, B:0, C:0, D:0> <A:0, B:0, C:0, D:0> <A:0, B:0, C:0, D:0> <A:1, B:0, C:0, D:0> <A:2, B:0, C:0, D:0> <A:1, B:0, C:1, D:0> <A:1, B:0, C:1, D:0>
31. ABCD AB CD D BC A BCD Partition Graph T2 <A:0, B:0, C:0, D:0> <A:0, B:0, C:0, D:0> <A:0, B:0, C:0, D:0> <A:1, B:0, C:0, D:0> <A:2, B:0, C:0, D:0> <A:1, B:0, C:1, D:0> <A:1, B:0, C:1, D:0> ABCD
32. ABCD AB CD D BC A BCD ABCD Partition Graph T2 <A:0, B:0, C:0, D:0> <A:0, B:0, C:0, D:0> <A:0, B:0, C:0, D:0> <A:1, B:0, C:0, D:0> <A:2, B:0, C:0, D:0> <A:1, B:0, C:1, D:0> <A:1, B:0, C:1, D:0> Conflict!
33. Conflict Resolution “A conflict detection mechanism, while valuable, has increased effect if there is also a method for reconciling conflicts automatically”
35. Bayou Summary System designed for weak connectivity Eventual consistency via application- defined dependency checks and developer defined merge procedures Epidemic algorithms to replicate state
36. “Applications must be aware of and integrally involved in conflict detection and resolution” Terry et. al
37. Bayou Take aways & thoughts “Humans would rather deal with the occasional unresolvable conflict than incur the adverse impact on availability”
39. CAP Theorem PARTITION TOLERANCE CONSISTENCY AVAILABILITY
40. Consistency Models Linearizable Sequential Causal Pipelined random access memory Read your write Monotonic read Monotonic write Write from read CP Consistency AP Consistency
42. CRDTs Summary Mathematical properties & epidemic algorithms / gossip protocols Strong Eventual Consistency - apply updates immediately, no conflicts, or rollbacks via
43. CRDTs * Stolen from Chris Meiklejohn in practice
44. Applying rollbacks is hard Restrict operation space to get provably convergent systems Active area of research Resolving Conflicts
45. Applying rollbacks is hard Restrict operation space to get provably convergent systems Active area of research Resolving Conflicts
47. Feral mechanisms for keeping DB integrity Application-level mechanisms Analyzed 67 open source Ruby on Rails Applications Unsafe > 13% of the time 
 (uniqueness & foreign key constraint violations)
48. Concurrency control is hard! Availability is important to application developers Home-rolling your own concurrency control or consensus algorithm is very hard and difficult to get correct!
49. Eventual Consistency We want highly available systems so we must use weaker forms of consistency (remember CAP) Application semantics helps us make better tradeoffs Do not recreate the wheel, leverage existing research allows us to not repeat past mistakes Forced into a feral world but this may change soon! Tl;DR
50. @Caitie Thank you!
51. @Caitie Thank you! Follow your dreams!