This document discusses Conflict-free Replicated Data Types (CRDTs) and their real-world uses. It begins by describing the distributed counter problem and consistency challenges. It then introduces various CRDT approaches like G-Counter, PN-Counter, MV-Register, OR-Set, and their properties. Finally, it provides examples of how CRDTs are used in systems like Cassandra, Riak, TomTom navigators, Swarm.js, and Spark accumulators to allow for replication and convergence of concurrent changes across distributed nodes.

1. CRDT Data Structures
And their real world uses

2. Distributed counter (motivation example)
Problem
20 20
+1 +1
21 21 21 21

3. The problem
Several active servers
Semi-online systems (navigators, sales support software)
Distributed systems (replication in general)

4. Consistency
… all nodes see the same data at the same time ..
A A
Consistency has costs

5. Consistency
Eventual consistency
“ …. eventually all accesses to that item will return the last updated value … “
Strong eventual consistency
“... any two nodes that have received the same (unordered) set of updates will be in the same state … “

6. CRDT
Conflict-free Replicated Data Type
CvRDT (Convergent) aka 'state-based objects'
CmRDT (Commutative) aka 'ops-based objects'

7. First CRDT: G-Counter
{a:4,b:5} {a:4,b:5}
+1 +1
{a:5,b:5} {a:4,b:6} {a:5,b:6} {a:5,b:6}
Value of the counter - sum of all parts

8. CRDT counter: alternative
20 20
+1 +1
21 21
+1
+1
22 22

9. G-Counter extension: PN-Counter
What if decrement operation is also required?
Use two g-counters: one for increments, another for decrements

10. State based vs ops based
State based:
Merge should be: associative, commutative and idempotent
(A ⨂ B) ⨂ C= A ⨂ (B ⨂ C) max(max(1, 2), 3) = max(1, max(2, 3))
A ⨂ B = B ⨂ A max(1, 2) = max(2, 1)
A ⨂ B = A ⨂ B ⨂ B max(1, 2) = max(max(1, 2), 2)

11. State based vs ops based
Ops based:
Replication channels should have exactly-once semantic and support causal
ordering
21 21
+1
Concurrent operations should commute
A B
C D

12. Example: Cassandra
Cassandra’s distributed counters are implemented as PN-counters (almost)
Cassandra’s general replication is implemented as another CRDT (LWW-Register)
(data1,12) (data2,14) (data2,14) (data2,14)

13. MV-Register (multi value)
Vector clock
Very similar to g-counter - {a:100, b: 98, c: 101}
Each operation on server increments corresponding value
Merge takes maximum of correlated elements
One event is AFTER another if vector clock of one is less than vector clock
of another:
{a: 10, b: 11, c: 12} < {a:10, b:12, c:12}

14. MV-Register
Value is stored and replicated with vector clock
On merge if one vector clock is bigger than another then keep value with
bigger vector clock
Otherwise keep both and let client choose which one to keep

15. Example: Riak
It uses MV-Register for general replication if multi-value mode is enabled
It uses LWW-Register otherwise
PN-counter is used to implement distributed counters
Other CRDTs are also used (Sets, flags)

16. G-Set (Grow only)
Merge operation is set union, which is idempotent, commutative and associative
Only add operation is supported

17. OR-Set (observed remove)
Idea is to use two sets for added and removed items, but...
Store them with some unique id. Such id should be assigned during adding of
element
(a, id1)
(a, id2)
(b, id3)
(c, id4)
‘Added’ Set
(b, id3)
‘Removed’ Set
(a, id2)
Element is eligible to remove only if it is in ‘added’ set with same id

18. Real life example: TomTom (navigators)
Challenges:
Account data (like favorites) can be modified from different devices
concurrently
Device can be offline during adding new information
Huge number of accounts

19. Real life example: TomTom (navigators)
CRDT to rescue!
They use combination of CRDT: MV-Register + modified OR-Set (OUR-Set)
*Original image from TomTom’s presentation

20. Real life example: Swarm.js
Swarm is a reactive data sync library and middleware
Swarm uses CRDT to merge data

21. Real life example: Spark’s accumulator
Docblock of Accumulable class
A data type that can be accumulated, ie has an commutative and associative "add" operation
You must define how to add data, and how to merge two of these together
It seems like CRDT!

22. Q/A