Eventually Consistent
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The document discusses different consistency models including: - Eventual consistency, where updates will propagate across replicas given time but not immediately. - Causal consistency, where updates respect causality and are guaranteed to be seen in the order they occurred. - Read-your-writes consistency, where a process sees its own writes. It also covers optimizations for read and write operations and design considerations like clients implementing consistency through versioning.
Eventually Consistent
- 1. Eventually Consistent wspringer@xebia.com woensdag 21 juli 2010
- 2. Werner Vogels woensdag 21 juli 2010
- 3. ‘60s ‘90s Distribution Minimize Transparency Failure woensdag 21 juli 2010
- 4. Client Perspective woensdag 21 juli 2010
- 5. Model B A C woensdag 21 juli 2010
- 6. Strong Consistency 1 0 value = "foo" value = "bar" 2 B A value = "bar" 2 C 2 value = "bar" value = "bar" After the update, any subsequent access will return the updated value. woensdag 21 juli 2010
- 7. Weak Consistency B 0 value = "foo" >1 1 value = "bar" A value = "bar" / "foo" >1 C value = "bar" / value = "bar" / "foo" >1 "foo" The system does not guarantee that at any given point in the future subsequent access will return the updated value woensdag 21 juli 2010
- 8. Eventual Consistency B 0 value = "foo" 1 value = "bar" t A value = "bar" t C value = "bar" t value = "bar" t≥1 If no updates are made to the object, eventually all accesses will return the last updated value. woensdag 21 juli 2010
- 9. Causal Consistency 2 notification of update B 0 value = "foo" 1 value = "bar" 3 A value = "bar" 3 C value = "foo" Subsequent access by process B will return the updated value, and a write is guaranteed to supersede the earlier write. woensdag 21 juli 2010
- 10. Read-your-writes Consistency B 0 value = "foo" 1 value = "bar" A C 2 value = "bar" Process A, after updating a data item always access the updated value and never sees an older value woensdag 21 juli 2010
- 11. Session Consistency B Session 1 0 value = "foo" 1 value = "bar" A 2 value = "bar" 2 value = "foo" C Session 2 Within the “session”, the system guarantees read-your- writes consistency woensdag 21 juli 2010
- 12. Monotonic Read Consistency B 0 value = "foo" value = "bar" A 3 1 value = "foo" C 2 value = "foo" 4 value = "bar" If a process has seen a particular value for the object, any subsequent access will never return any previous values woensdag 21 juli 2010
- 13. Monotonic Write Consistency B 0 value = "foo" A value = "bar" 1 2 C value = "last" The system guarantees to serialize the writes by the same process woensdag 21 juli 2010
- 14. Eventual Consistentency in RDBMS Log shipping Primary Backup replica A 1 async 2 3 Eventual consistency is not just a property of NoSQL Solutions woensdag 21 juli 2010
- 15. Server Perspective woensdag 21 juli 2010
- 16. NRW N The number of nodes that store replicates of the data W The number of replicas that need to acknowledge the receipt of the update before the update completes R The number of replicas that are contacted when a data object is accessed through a read operation woensdag 21 juli 2010
- 17. Strong Consistency W=3 value = "foo" value = "foo" A value = "foo" N=4 value = "foo" R=2 W + R > N implies strong consistency woensdag 21 juli 2010
- 18. Optimizations • Optimize read: R = 1, N = W • Optimize write: W = 1, N = R woensdag 21 juli 2010
- 19. Design Considerations • Clients implementing read-your-writes and monotonic reads, by adding versions on writes, and discarding everything the precedes the last-seen version. woensdag 21 juli 2010