1. Concurrency Control in Distributed Databases. By :- Rishikesh Mandvikar rmandvik[at]engr.smu.edu May 1, 2004

2. 2 Topics Serializability Theory  Centralized Databases  Distributed Databases Lock Based Concurrency Control Algorithms  Centralized (2PL, S2PL)  Distributed (C2PL, PC2PL, D2PL) Optimistic Concurrency Control

3. 3 Serializability Theory [13]

4. 4

5. 5 Serializability Theory extended to Distributed Database [14] Fragmentation  Horizontal  Vertical  Hybrid Replication  Synchronous Replication ROWA Protocol Voting  Asynchronous Replication

6. 6 Classification of CC Algorithms [14]

7. 7 Locking based CC Algorithms Centralized  2PL (Relaxed S2PL)  S2PL Distributed  C2PL  PC2PL  D2PL

8. 8 2 Phase locking (2PL) [13] Rules: Growing phase:  “A txn that has to read/write a data object first has to request a read/write lock on it.” Shrinking phase:  “A txn cant request additional locks once it releases a lock.”

9. 9 Lock Graph for 2PL

10. 10 Strict 2 Phase Locking (S2PL) [13] Rules: Growing phase:  “A txn that has to read/write a data object first has to request a read/write lock on it.” Non - Shrinking phase:  “Txn releases all locks only when it completes.”

11. 11 Lock Graph for S2PL

12. 12 2PL, S2PL [13]

13. 13 2PL, S2PL Differences  2PL Cascading aborts Conflict serializable schedules (not all) High concurrency  S2PL No cascading aborts Serializable schedules Low concurrency

14. 14 Centralized 2PL

15. 15 Centralized 2PL [14] Cons  Failure of primary site  Bottleneck situation  Communication links

16. 16 Primary Copy 2PL [14] Lock on primary copy necessary Lock management at the primary-copy sites only Pros  Reduces load at central site Cons  Deadlock handling is partially centralized

17. 17 Distributed 2PL [14]

18. 18 Distributed 2PL [14] Pros  Lock management independency Cons  Complex deadlock handling required  Communication cost

19. 19 Optimistic Concurrency Control [13][14]  Txns assumed to have no conflicts  Private workspace area  Validation of txns before write phase

20. 20 Optimistic Concurrency Control [13][14] Txn phases:  Read and Compute read from database and write into private workspace  Validate Timestamps assigned over here Check for conflict with concurrent txns  Write Copy into database if validation successful

21. 21 Optimistic Concurrency Control [13][14] For Ti and Tj where TS(Ti) < TS(Tj) Validation Criteria  All phases of Ti execute before Tj  Ti ends before write phase of Tj and Ti doesn’t modify data read by Tj  Ti finishes its read phase before Tj finishes its read phase and they both don’t read/write any common data

22. 22 Optimistic Concurrency Control [13][14] Validation  For validating Tj w.r.t committed txn Ti where TS(Ti) < TS(Tj) Maintain a list of read/write object list for Tj Other cant commit while Tj is validated Once Validated, write phase allowed to finish Bottleneck situation

23. 23 Optimistic Concurrency Control [13][14] Advantages  Increased concurrency with a good “mix” of txns.  Better than Lock based systems Disadvantages  Bottleneck situation  Maintaining read/write list for every txn  Copying the private space to the database  Long txns

24. 24 Optimistic Concurrency Control [13][14] Disadvantages  Long txns Read/write list would be very long Chance of Restart is proportional to the square of its size [9]

25. 25 Research Optimistic CC algorithm  IBM’s IMS FASTPATH (Centralized DBMS)  OCC in Distributed DBMS

26. 26 Conclusion Serializability Theory Lock Based Systems Optimistic CC algorithms Timestamp Ordering

27. 27 Questions??