Chapter 15: Transactions

1. Chapter 15: Transactions • Transaction Concept • Transaction State • Implementation of Atomicity and Durability • Concurrent Executions • Serializability • Recoverability • Implementation of Isolation • Transaction Definition in SQL • Testing for Serializability.

2. Transaction Concept • Transaction • a collection of read/write operations to perform a logcial unit of work • E.g., transaction to transfer $50 from account A to B: 1. read(A) 2. A := A – 50 3. write(A) 4. read(B) 5. B := B + 50 6. write(B) • Consistency requirement – the sum of A and B shoule not change due to the execution of the transaction • Atomicity requirement — if the transaction fails after step 3, the system should ensure that its updates are not reflected in the database.

3. ACID Properties To preserve integrity of data, the database system must ensure: • Atomicity: Either all operations of the transaction are properly reflected in the database or none are. • Consistency: Execution of a transaction in isolation preserves the consistency of the database. • Isolation: Each transaction must be unaware of other concurrently executing transactions. Intermediate transaction results must be hidden from other concurrently executed transactions. • For every pair of transactions Tiand Tj, it appears to Tithat either Tj, finished execution before Ti started, or Tj started execution after Ti finished. • Durability: After a transaction completes successfully, the changes it has made to the database persist, even if there are system failures.

4. Example of Fund Transfer (Cont.) • Durability requirement • Once the user has been notified that the transaction has completed (i.e., the transfer of the $50 has taken place), the updates to the database by the transaction must persist despite failures • Isolation requirement • If another transaction is allowed to access the partially updated database between steps 3 and 6, it will see an inconsistent database • The sum A + B will be less than it should be • Trivial solution: Run transactions serially • Performance degradation

5. Transaction State

6. Implementation of Atomicity and Durability Shadow-database scheme: • Assumes disks do not fail • Extremely inefficient for large databases: executing a single transaction requires copying the entire database. • Logging & recovery (Chapter 17)

7. Concurrent Executions • Advantages of concurrent executions • Higher throughput • One transaction does I/O, another uses CPU • Reduced average response time • Short transactions do not have to wait long ones • Concurrency control schemes • Achieve isolation • Control the interaction among the concurrent transactions in order to prevent them from destroying the consistency of the database • Serializability: concurrent execution is equal to some serial execution

8. Example (Serial) Schedules • Let T1 transfer $50 from A to B, and T2 transfer 10% of the balance from A to B.

9. Example Schedule (Cont.) • Not a serial schedule, but equivalent to the serial schedule In both Schedule 1 and 3, the sum A + B is preserved.

10. Example Schedules (Cont.) • The following concurrent schedule does not preserve the value of the the sum A + B.

11. Serializability • Basic Assumption • Each transaction preserves database consistency. • Serial execution preserves consistency • A schedule is serializable if it is equivalent to a serial schedule. 1. conflict serializability 2. view serializability • Consider read write operations only

12. Conflict Serializability • Instructions li and lj of transactions Ti and Tj respectively, conflict if and only if both li and lj access some data item Q, and at least one of them is write(Q). 1. li = read(Q), lj = read(Q): No conflict.2. li = read(Q), lj = write(Q): Conflict.3. li = write(Q), lj = read(Q): Conflict4. li = write(Q), lj = write(Q): Conflict • If a schedule S can be transformed into a schedule S´ by swapping of non-conflicting instructions, S and S´ are conflict equivalent. • A schedule S is conflict serializable if it is conflict equivalent to a serial schedule.

13. Conflict Serializability (Cont.) • Not conflict serializable T3T4read(Q)write(Q)write(Q)Can not swap instructions to obtain either the serial schedule < T3, T4 >, or the serial schedule < T4, T3 >.

14. Conflict Serializability (Cont.) • Conflict serializable to a serial schedule <T2, T1> • Swap non-conflicting instructions

15. View Serializability • Let S and S´ be two schedules with the same set of transactions. S and S´ are view equivalentif: 1. For each data item Q, if transaction Tireads the initial value of Q in schedule S, then transaction Ti must, in schedule S´, also read the initial value of Q. 2. For each data item Q if transaction Tiexecutes read(Q) in schedule S, and that value was produced by transaction Tj(if any), then transaction Ti must in schedule S´ also read the value of Q that was produced by transaction Tj . 3. For each data item Q, the transaction (if any) that performs the final write(Q) operation in schedule S must perform the finalwrite(Q) operation in schedule S´.

16. View Serializability (Cont.) • A schedule S is view serializable if it is view equivalent to a serial schedule <T3, T4, T6>. • Every conflict serializable schedule is also view serializable • A schedule which is view-serializable but not conflict serializable: • Every view serializable schedule, which is not conflict serializable, has blind writes • More concurrency than conflict serializability, howerver, NP-complete

17. Other Notions of Serializability • Schedule 8 (from text) given below produces same outcome as the serial schedule < T1,T5 >, yet is not conflict equivalent or view equivalent to it. • Determining such equivalence requires analysis of operations other than read and write.

18. Recoverability Need to address the effect of transaction failures on concurrently running transactions. • Recoverableschedule: if Tk reads a data item previously written by Tj ,Tjshould commit before Tk commits. • The following schedule is not recoverable if T9commits immediately after the read • If T8should abort, T9 would have read (and possibly shown to the user) an inconsistent database state. Hence database must ensure that schedules are recoverable.

19. Recoverability (Cont.) • Cascading rollback • A single transaction failure leads to a series of transaction rollbacks • Assume no transaction has committed (so the schedule is recoverable) • If T10 fails, T11 and T12 must also be rolled back. • Possibly undo a significant amount of work

20. Recoverability (Cont.) • Cascadelessschedules • Cascading rollbacks cannot occur; for each pair of transactions Tjand Tk such that Tk reads a data item previously written by Tj, the commit operation of Tj appears before the read operation of Tk. • Every cascadeless schedule is also recoverable • Stricter than recoverable schedules • Avoid cascading aborts

21. Implementation of Isolation • Objective: • Schedules must be conflict or view serializable, and recoverable for consistency • Preferably cascadeless • Supported by concurrency control

22. Testing for Serializability • Consider some schedule of a set of transactions T1, T2, ..., Tn • Precedence graph • Draw an arc from Tito Tjif the two transaction conflict, and Tiaccessed the data item on which the conflict arose earlier. • Example 1

23. Example Schedule (Schedule A) T1 T2 T3 T4 T5 read(X)read(Y)read(Z) read(V) read(W) read(W) read(Y) write(Y) write(Z)read(U) read(Y) write(Y) read(Z) write(Z) read(U)write(U)

24. Precedence Graph for Schedule A T1 T2 T4 T3

25. Test for Conflict Serializability • A schedule is conflict serializable iff its precedence graph is acyclic. • Cycle-detection algorithms O(n2) where n is the number of vertices in the graph. • If precedence graph is acyclic, the serializability order can be obtained by a topological sorting of the graph. For example, a serializability order for Schedule A would beT5T1T3T2T4.

26. Test for View Serializability • The precedence graph test for conflict serializability must be modified to apply to a test for view serializability. • The problem of checking if a schedule is view serializable falls in the class of NP-complete problems. Thus existence of an efficient algorithm is unlikely.However practical algorithms that just check some sufficient conditions for view serializability can still be used.

27. Concurrency Control vs. Serializability Tests • Too late to test the serializability after a schedule has been executed • Develop concurrency control protocols that will assure serializability • Do not examine the precedence graph; instead • Impose disciplines that avoids nonseralizable schedules • Serializability test help understand why a concurrency control protocol is correct.

28. End of Chapter