Spanner Database Overview

Spanner is a globally distributed database system that offers configurable control, consistent commit timestamps, external consistency, and TrueTime API for handling distributed data. It uses a transaction model with two-phase locking and lock-free reads, providing globally sortable timestamps. The system ensures external consistency by ordering commit timestamps and enforcing a real-world approximation of global wall-clock time consistency. Supported read/write operations include Paxos writes, commit waits, and various read variants to ensure data consistency and reliability.

• Spanner Database
• Globally Distributed Data
• Consistency Model
• TrueTime API
• Distributed Transactions

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Presentation Transcript

1. Spanner Lixin Shi 6.033 Quiz2 Review (Some slides from Spanner s OSDI presentation)

2. Key Points to Remember Major Claims Globally distributed data with configurable control Consistent commit timestamps Consistency Model: external consistency TrueTime API Set of supported read/write operations Paxos write Relaxed read w/wo time stamp

3. Globally Distributed Data Cross-Datacenter Distribution User Configurable

4. Transaction Model Two-Phase locking with start/commit Transactional write and lock-free read Globally sortable time stamp with each commit Bounded error between time stamp and wall- clock time start commit t T1: s1 s1: Timestamp

5. External Consistency If a transaction T1 commits before another transaction T2 starts, then T1's commit timestamp is smaller than T2 A real-world approximation of global wall- clock time consistency start commit start commit t t T1: s1 T1: s1 T2: s2 T2: s2 x s1 < s2 s1 < s2

6. TrueTime API Global wall-clock time with bounded uncertainty TT.now() time earliest latest 2*

7. Commit Wait Acquired locks Release locks T Pick s = TT.now().latest s Wait until TT.now().earliest > s Commit wait average average What this gives you: absolute start time < s < absolute commit time

8. From TrueTime to Consistency Recall: what TrueTime gives you: start commit t T1: s1 s1 needs to be in this range If there are two transactions: start commit s1 < s2 t T1: s1 T2: s2 s1 range s2 range

9. Supported Read/Write Operations Read-Write transaction Paxos write Commit wait Read transaction with timestamp s Lock-free Every replica tracks tsafe Read from any replica with tsafe >= s Other variants of read Standalone read: read with t.now().latest Read with bounded timestamp

10. GFS Lixin Shi 6.033 Quiz2 Review (Some slides from GFS s SOSP presentation)

11. Design Assumption/Facts Hardware fails very often. Large files (>=100MB) are typical. For read operations: large streaming reads + small random reads. For write operations: Record appends are the prevalent form of writing. Need to handle concurrency. Design choice: high bandwidth >> low lantency

12. Architecture

13. Read Algorithm

14. Read Algorithm (cont.)

15. Write Algorithm

16. Write Algorithm (cont.)

17. Write Algorithm (cont.)

18. Write Algorithm (cont.)

19. Atomic Record Appends Atomic! A few changes from the write algorithm: