Transactions in dbms
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The document discusses transaction concepts in database systems. It defines transactions as units of program execution that access and update database items. Transactions must satisfy the ACID properties of atomicity, consistency, isolation, and durability. Concurrent transaction execution allows for increased throughput but requires mechanisms to ensure serializability and recoverability. The document describes transaction states, schedule serializability testing using precedence graphs, and the goal of concurrency control protocols to enforce serializability without examining schedules after execution.
Transactions in dbms
- 2. Transaction Concept Transaction Properties Transaction States Concurrent Executions Serializability of Schedules Recoverability of Schedules Testing for Serializability.
- 3. A transaction is a unit of program execution that accesses and possibly updates one or more data items in the database. A group of tasks where task is a minimum processing unit which cannot be divided further. Two main issues to deal with: ◦ Failures of various kinds, such as hardware failures and system crashes ◦ Concurrent execution of multiple transactions
- 4. 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. Although multiple transactions may execute concurrently, each transaction must be unaware of other concurrently executing transactions. Intermediate transaction results must be hidden from other concurrently executed transactions. ◦ That is, for every pair of transactions Ti and Tj, it appears to Ti that 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. To preserve integrity of data, the database system must ensure:
- 5. Transaction to transfer $50 from account A to account 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 is unchanged by the execution of the transaction. Atomicity requirement — if the transaction fails after step 3 and before step 6, the system should ensure that its updates are not reflected in the database, else an inconsistency will result.
- 6. 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 between steps 3 and 6, another transaction is allowed to access the partially updated database, it will see an inconsistent database (the sum A + B will be less than it should be). Can be ensured trivially by running transactions serially, that is one after the other.
- 7. Active, the initial state; the transaction stays in this state while it is executing Partially committed, after the final statement has been executed. Failed, after the discovery that normal execution can no longer proceed. Aborted, after the transaction has been rolled back and the database restored to its state prior to the start of the transaction. Two options after it has been aborted: ◦ restart the transaction – only if no internal logical error ◦ kill the transaction Committed, after successful completion.
- 9. The recovery-management component of a database system implements the support for atomicity and durability. The shadow-database scheme: ◦ assume that only one transaction is active at a time. ◦ a pointer called db_pointer always points to the current consistent copy of the database. ◦ all updates are made on a shadow copy of the database, and db_pointer is made to point to the updated shadow copy only after the transaction reaches partial commit and all updated pages have been flushed to disk. ◦ in case transaction fails, old consistent copy pointed to by db_pointer can be used, and the shadow copy can be deleted.
- 10. Assumes disks to not fail Useful for text editors, but extremely inefficient for large databases: executing a single transaction requires copying the entire database. The shadow-database scheme:
- 11. Multiple transactions are allowed to run concurrently in the system. Advantages are: ◦ increased processor and disk utilization, leading to better transaction throughput: one transaction can be using the CPU while another is reading from or writing to the disk ◦ reduced average response time for transactions: short transactions need not wait behind long ones.
- 12. Schedules – sequences that indicate the chronological order in which instructions of concurrent transactions are executed ◦ a schedule for a set of transactions must consist of all instructions of those transactions ◦ must preserve the order in which the instructions appear in each individual transaction.
- 13. Basic Assumption – Each transaction preserves database consistency. Thus serial execution of a set of transactions preserves database consistency. A (possibly concurrent) schedule is serializable if it is equivalent to a serial schedule.
- 14. Let T1 transfer $50 from A to B, and T2 transfer 10% of the balance from A to B. The following is a serial schedule, in which T1 is followed by T2. Schedule 1
- 15. Let T1 and T2 be the transactions defined previously. The following schedule 2 is not a serial schedule, but it is equivalent to Schedule 1. In both Schedule 1 and 2, the sum A + B is preserved. Schedule 2
- 16. The following concurrent schedule does not preserve the value of the sum A + B. Schedule 3
- 17. Instructions li and lj of transactions Ti and Tj respectively, conflict if and only if there exists some item Q accessed by both li and lj, and at least one of these instructions wrote Q. 1. li = read(Q), lj = read(Q). li and lj don’t conflict. 2. li = read(Q), lj = write(Q). They conflict. 3. li = write(Q), lj = read(Q). They conflict 4. li = write(Q), lj = write(Q). They conflict Intuitively, a conflict between li and lj forces a (logical) temporal order between them. If li and lj are consecutive in a schedule and they do not conflict, their results would remain the same even if they had been interchanged in the schedule.
- 18. If a schedule S can be transformed into a schedule S´ by a series of swaps of non-conflicting instructions, we say that S and S´ are conflict equivalent. We say that a schedule S is conflict serializable if it is conflict equivalent to a serial schedule Example of a schedule that is not conflict serializable: T3 T4 read(Q) write(Q) write(Q) We are unable to swap instructions in the above schedule to obtain either the serial schedule < T3, T4 >, or the serial schedule < T4, T3 >.
- 19. Schedule 4 below can be transformed into a serial schedule where T2 follows T1, by series of swaps of non-conflicting instructions. Therefore Schedule 4 is conflict serializable. Schedule 4
- 20. Recoverable schedule — if a transaction Tj reads a data items previously written by a transaction Ti , the commit operation of Ti appears before the commit operation of Tj. The following schedule (Schedule 5) is not recoverable if T9 commits immediately after the read If T8 should abort, T9 would have read (and possibly shown to the user) an inconsistent database state. Hence database must ensure that schedules are recoverable. Need to address the effect of transaction failures on concurrently running transactions. Schedule 5
- 21. Cascading rollback – a single transaction failure leads to a series of transaction rollbacks. Consider the following schedule where none of the transactions has yet committed (so the schedule is recoverable) If T10 fails, T11 and T12 must also be rolled back. Can lead to the undoing of a significant amount of work
- 22. Consider some schedule of a set of transactions T1, T2, ..., Tn Precedence graph — a direct graph where the vertices are the transactions (names). We draw an arc from Ti to Tj if the two transaction conflict, and Ti accessed the data item on which the conflict arose earlier. We may label the arc by the item that was accessed. Example Cycle in the graph represents conflict in schedule. x y
- 23. 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. T3 T4 T1 T2
- 25. A schedule is conflict serializable if and only if its precedence graph is acyclic. If precedence graph is acyclic, the serializability order can be obtained by a topological sorting of the graph. E.g. a serializability order for Schedule A is T5 → T1 → T3 → T2 → T4 .
- 26. Testing a schedule for serializability after it has executed is a little too late! Goal – to develop concurrency control protocols that will assure serializability. They will generally not examine the precedence graph as it is being created; instead a protocol will impose a discipline that avoids nonseralizable schedules.
Editor's Notes
- #6: Let initial values of A=100 and B=50. Initial Sum, A + B=150 A=A-50=50, B=B+50=100. Final Sum, A + B= 150 Initial Sum= Final Sum (Consistency Preserved)
- #15: Let initial values of A=100 and B=50. Initial Sum, A + B=150 T1: A=A-50=50, B=B+50=100. Final Sum, A + B= 150 T2: Temp= 10% of A=5 A=A-temp=50-5=45 B=B+temp=100+5=105 Final Sum, A+B=150 (Consistency Preserved)
- #16: Schedule 2: A=A-50=50 A=A-temp=45 B=B+50=100 B=B+temp=105 Final sum, A+B=150 (Consistency Preserved)
- #17: Schedule 3: temp=10% of A=10 A=A-temp=100-10=90 A=100-50=50 B=50+50=100 B=B+temp=50+10=60 Final Sum, A+B=50+60=110