recoverability and serializability dbms

recoverability and serializability dbms

1. TOPIC : - Characterizing Schedules Based on Recoverability and Serializability.

2. SCHEDULE ▶ A schedule (or history ) S of n transactions T1 , T2 , …, Tn is an ordering of the operations of the transactions, such that operations of Ti in S must appear in the same order in which they occur in Ti . ▶ For example, the schedule of T1 and T2 is ▶ S : r1(X); r2(X); w1(X); r1(Y); w2(X); w1(Y);

3. ▶ Two operations in a schedule are conflict if: They belong to different transactions, They access the same item X, and At least one of them is a WRITE_ITEM(X) operation. ▶ A schedule S of n transactions T 1 , T 2 , …, T n is said to be a complete schedule if: The operations in S are exactly those operations in T 1 , T 2 , …, T n including a commit or abort operation as the last operation for each transaction. The order of operations in S is the same as their occurrence in T i . For any two conflict operations, one of the two must occur before the other in the schedule.

4. Characterizing Schedules Based on Recoverability. ▶ We would like that, once a transaction T is committed, it should never be necessary to roll back T. The schedules that meet this criterion are called recoverable schedules . Therefore: A schedule S is recoverable if no transaction T in S commits until all transactions T’ that have written an item that T reads have committed. For example S’ a : r 1 (X); r 2 (X); w 1 (X); r 1 (Y); w 2 (X); c 2 ; w 1 (Y); c 1 ; is recoverable, even though it suffers from the lost update problem.

5. ▶ E x ample - - Co n sider t h e fol l owing sche d ules: Sc : r1(X); w1(X); r2(X);r1(Y); w2(X); c2; a1 ; Sd : r1(X);w1(X); r2(X);r1(Y); w2(X); w1(Y); c1; c2 ; Se : r1(X); w1(X); r2(X);r1(Y); w2(X); w1(Y); a1 ; a2 ; Sc is not recoverable , because T2 reads item X written by T1 , and then T2 commits before T1 commits. Sd is recoverable , because T2 reads item X written by T1 , and then T2 commits after T1 commits and no other conflict operations exists in the schedule. Se is similar to Sd , but T 1 is aborted (instead of commit). In this situation T2 should also abort, because the value of X it read is no longer valid (this phenomenon known as cascading rollback or cascading abort ).

6. ▶ Because cascading rollback can be quite time-consuming, we perform cascade less schedules. ▶ A schedule is said to be cascade less or to avoid cascading rollback if every transaction in the schedule reads only items that were written by committed transactions. ▶ A more restrictive type of schedule is called strict schedule, in which transactions can neither read nor write an item X until the last transaction that wrote X has committed (or aborted)

7. Characterizing Schedules Based on Serializability ▶ If no interleaving of operations is permitted, there are only two possible arrangements for executing transactions T1 and T2 : ▶ Execute (in sequence) all the operations of transaction T1, followed by all the operations of transaction T2. ▶ Execute (in sequence) all the operations of transaction T2, followed by all the operations of transaction T1. ▶ If interleaving of operations is allowed there will be many possible schedules. ▶ The concept of serializability of schedules is used to identify which schedules are correct.

8. ▶ Examples of serial and non-serial schedules involving transactions T 1 and T 2 . Serial schedule A: T1 followed by T2 . Serial schedules B: T2 followed by T1 .

9. (c) Two Non-serial schedules C and D with interleaving of operations.

10. ▶ A schedule S is serial , if for every transaction T participating in the schedule, all the operations of T are executed consecutively in the schedule; otherwise the schedule is called non-serial. ▶ The drawback of serial schedules is that they limit concurrency of interleaving of operations. ▶ Two schedules are called result equivalent if they produce the same final state of the database.

11. ▶ Example : Two schedules that are result equivalent for the initial value of X = 100, but are not result equivalent in general.

12. ▶ Two schedules are called Conflict equivalent if the order of any two conflicting operations is the same in both schedules. ▶ A schedule S of n transactions is Serializable if it is equivalent to some serial schedule of the same n transactions. ▶ A schedule S to be conflict serializable if it is conflict equivalent to some serial schedule S’.

13. ▶ Algorithm for testing conflict serializability of S: For each transaction Ti in schedule S, create a node, If Tj executes a READ_ITEM(X) after Ti executes a WRITE_ITEM(X), create an edge Ti->Tj If Tj executes a WRITE_ITEM(X) after Ti executes a READ_ITEM(X), create an edge Ti->Tj If Tj executes a WRITE_ITEM(X) after Ti executes a WRITE_ITEM(X), create an edge Ti->Tj The schedule S is serializable if and only if the precedence graph has no cycle.

14. TOPIC:- LOCK BASED PROTOCOLS PRESENTED BY:- N A M E :- S A T Y A PRA K ASH RANJAN ROLL NO:- MCA/25005/18

15. LOCK BASED PROTOCOLS ▶ A lock is a mechanism to control concurrent access to a data item Data items can be locked in two modes : 1. exclusive (X) mode . Data item can be both read as well as written. X-lock is requested using lock-X instruction. 2. shared (S) mode . Data item can only be read. S-lock is requested using lock-S instruction. ▶ Lock requests are made to concurrency-control manager. Transaction can proceed only after request is granted.

16. Lock-Based Protocols (Cont.) ▶ A transaction may be granted a lock on an item if the requested lock is compatible with locks already held on the item by other transactions ▶ Any number of transactions can hold shared locks on an item, but if any transaction holds an exclusive on the item no other transaction may hold any lock on the item. ▶ If a lock cannot be granted, the requesting transaction is made to wait t i ll all incom p at i bl e lo c k s held b y o t her transact i ons have b e en r eleas e d . T h e lock is then granted. Lock-compatibility matrix

17. P itfa l s o f Loc k -B a s e d P roto c o l s ▶ Consider the partial schedule Neither T 3 nor T 4 can make progress — executing lock-S (B) causes T 4 to wait for T 3 to release its lock on B , while executing lock-X (A) causes T 3 to wait for T 4 to release its lock on A . Such a situation is called a deadlock . To handle a deadlock one of T 3 or T 4 must be rolled back and its locks released.

18. Pitfalls of Lock-Based Protocols (Cont.) ▶ The potential for deadlock exists in most locking protocols. Deadlocks are a necessary evil. ▶ Starvation is also possible if concurrency control manager is badly designed. For example: 🢐 A transaction may be waiting for an X-lock on an item, while a sequence of other transactions request and are granted an S-lock on the same item. 🢐 The same transaction is repeatedly rolled back due to deadlocks. ▶ Concurrency control manager can be designed to prevent starvation

19. The Two-Phase Locking Protocol ▶ T h i s i s a protocol w h ic h e n s ur e s confl i c t - s e rializabl e sc he dules . Ph a se 1: Growing Phase 🢐 transaction may obtain locks 🢐 transaction may not release locks ▶ Phase 2: Shrinking Phase 🢐 transaction may release locks 🢐 transaction may not obtain locks ▶ The protocol assures serializability. It can be proved that the transactions can be serialized in the order of their lock points (i.e. the point where a transaction acquired its final lock).

20. Th e T w o - P ha s e Lo c kin g Proto c o l (Cont.) ▶ Two-phase locking does not ensure freedom from deadlocks ▶ Cascading roll-back is possible under two-phase locking. To avoid this, follow a modified protocol called strict two-phase locking . Here a transaction must hold all its exclusive locks till it commits/aborts. ▶ Rigorous two-phase locking is even stricter: here all locks are held till commit/abort. In this protocol transactions can be serialized in the order in which they commit.

21. The Two-Phase Locking Protocol (Cont.) ▶ There can be conflict serializable schedules that cannot be obtained if two-phase locking is used. ▶ However, in the absence of extra information (e.g., ordering of access to data), two-phase locking is needed for conflict serializability in the following sense: ▶ Given a transaction T i that does not follow two-phase locking, we can find a transaction T j that uses two- phase locking, and a schedule for T i and T j that is not c o nflic t serializab l e.

22. L oc k C on v e rsi o n s ▶ Two-phase locking with lock conversions: First Phase: can acquir e a l o c k - S on ite m can acquir e a l o c k - X on ite m can c onv er t a l o c k - S t o a l o c k - X ( up gr ad e ) Second Phase: can release a lock-S can release a lock-X can c onv er t a l o c k - X to a l o c k - S ( d ow ng r ad e ) ▶ This protocol assures serializability. But still relies on the programmer to insert the various locking instructions.

23. Implementation of Locking ▶ A Lock manager can be implemented as a separate process to which transactions send lock and unlock requests ▶ The lock manager replies to a lock request by sending a lock grant messages (or a message asking the transaction to roll back, in case of a deadlock) ▶ The requesting transaction waits until its request is answered ▶ The lock manager maintains a data structure called a lock table to record granted locks and pending requests ▶ The lock table is usually implemented as an in-memory hash table indexed on the name of the data item being locked

24. TOPIC:- TIME STAMP-BASED PROTOCOLS PRESENTED BY:- NAME:- GAURAV PRAKASH ROLL NO:- MCA/25006/18

25. Timestamp-Based Protocols ▶ Each transaction is issued a timestamp when it enters the system. If an old transaction Ti has time-stamp TS(Ti), a new transaction Tj is assigned time-stamp TS(Tj) such that TS(Ti) <TS(Tj). ▶ The protocol manages concurrent execution such that the time-stamps determine the serializability order.

26. Timestamp-Based Protocols ▶ I n o r der t o assure such b e havi o r , t h e p r o t o c ol maintains for each data Q two timestamp values: W-timestamp(Q) is the largest time-stamp of any transaction that executed write(Q) successfully. R-timestamp(Q) is the largest time-stamp of any transaction that executed read(Q) successfully.

27. Timestamp-Based Protocols ▶ The timestamp ordering protocol ensures that any conflicting read and write operations are executed in timestamp order. ▶ Suppose a transaction Ti issues a read(Q) If TS(Ti) <_W-timestamp(Q), then Ti needs to read a value of Q that was already overwritten. Hence, the read operation is rejected, and Ti is rolled back. If TS(Ti) >_W-timestamp(Q), then the read operation is executed, and R-timestamp(Q) is set to the maximum of R- timestamp(Q) and TS(Ti).

28. Timestamp-Based Protocols Suppose that transaction Ti issues write(Q). If TS(Ti) < R-timestamp(Q), then the value of Q that Ti is producing was needed previously, and the system assumed that that value would never be produced. Hence, the write operation is rejected, and Ti is rolled back. If TS(Ti) < W-timestamp(Q), then Ti is attempting to write an obsolete value of Q. Hence, this write operation is rejected, and Ti is rolled back. Otherwise, the write operation is executed, and W- timestamp(Q) is set to TS(Ti).

29. Timestamp-Based Protocols ▶ The timestamp-ordering protocol guarantees serializability since all the arcs in the precedence graph are of the form: ▶ Thus, there will be no cycles in the precedence graph ▶ Timestamp protocol ensures freedom from deadlock as no transaction ever waits. ▶ But the schedule may not be cascade-free, and may not even be recoverable

30. Timestamp-Based Protocols ▶ Problem with timestamp-ordering protocol: ▶ Suppose Ti aborts, but Tj has read a data item written by Ti ▶ Then Tj must abort; if Tj had been allowed to commit earlier, the schedule is not recoverable . ▶ Further, any transaction that has read a data item written by Tj must abort ▶ This can lead to cascading rollback --- that is, a chain of rollbacks

31. Timestamp-Based Protocols Solution : ▶ A transaction is structured such that its writes are all performed at the end of its processing ▶ All writes of a transaction form an atomic action; no transaction may execute while a transaction is being written. ▶ A transaction that aborts is restarted with a new timestamp.

32. THE END.