PPT-concurrency Control database management system DBMS concurrent control (U5).pdf
- 1. Database Management System (SE IT 2019 Patt.) Faculty: Aruna K. Gupta JSPM’s Jayawantrao Sawant College of Engineering Department of Information Technology
- 2. Unit V Transaction and Concurrency Control CO5: Illustrate ACID properties for transaction management and describe concurrency control protocols. Topic: Concurrency Control TLO: To describe concurrency control protocols.
- 3. Outline Lock-Based Protocols Timestamp-Based Protocols Validation-Based Protocols
- 4. Lock-Based Protocols A lock is a mechanism to control concurrent access to a data i tem 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 the concurrency-control manager by the programmer. Transaction can proceed only after reque st is granted.
- 5. Lock-Based Protocols (Cont.) Lock-compatibility matrix A transaction may be granted a lock on an item if the requested lo ck is compatible with locks already held on the item by other trans actions 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 till all incompatible locks held by other transactions have bee n released. The lock is then granted.
- 6. Lock-Based Protocols (Cont.) Example of a transaction performing locking: T2: lock-S(A); read (A); unlock(A); lock-S(B); read (B); unlock(B); display(A+B) Locking as above is not sufficient to guarantee serializability — if A and B get updated in-between the read of A and B, th e displayed sum would be wrong. A locking protocol is a set of rules followed by all transacti ons while requesting and releasing locks. Locking protocols r estrict the set of possible schedules.
- 7. The Two-Phase Locking Protocol This protocol ensures conflict-serializable schedules. Phase 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 tran sactions can be serialized in the order of their lock points (i.e., t he point where a transaction acquired its final lock).
- 8. Deadlocks Consider the partial schedule Neither T3 nor T4 can make progress — executing lock-S(B) cause s T4 to wait for T3 to release its lock on B, while executing lock-X(A) causes T3 to wait for T4 to release its lock on A. Such a situation is called a deadlock. To handle a deadlock one of T3 or T4 must be rolled back and its locks released.
- 9. Deadlocks (Cont.) Two-phase locking does not ensure freedom from deadlocks. In addition to deadlocks, there is a possibility of starvation. Starvation occurs if the concurrency control manager is badly designed. For example: A transaction may be waiting for an X-lock on an item, whil e a sequence of other transactions request and are grante d an S-lock on the same item. The same transaction is repeatedly rolled back due to dea dlocks. Concurrency control manager can be designed to prevent starv ation.
- 10. Deadlocks (Cont.) The potential for deadlock exists in most locking protocols. De adlocks are a necessary evil. When a deadlock occurs there is a possibility of cascading roll- backs. Cascading roll-back is possible under two-phase locking. To av oid this, follow a modified protocol called strict two-phase loc king -- a transaction must hold all its exclusive locks till it com mits/aborts. Rigorous two-phase locking is even stricter. Here, all locks a re held till commit/abort. In this protocol transactions can be se rialized in the order in which they commit.
- 11. 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 gr ant 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 tabl e to record granted locks and pending requests The lock table is usually implemented as an in-memory hash ta ble indexed on the name of the data item being locked
- 12. Lock Table Dark blue rectangles indicate granted lock s; light blue indicate waiting requests Lock table also records the type of lock gr anted or requested New request is added to the end of the qu eue of requests for the data item, and gra nted if it is compatible with all earlier locks Unlock requests result in the request bein g deleted, and later requests are checked to see if they can now be granted If transaction aborts, all waiting or granted requests of the transaction are deleted lock manager may keep a list of locks held by each transaction, to impleme nt this efficiently
- 13. Deadlock Handling System is deadlocked if there is a set of transactions such that ev ery transaction in the set is waiting for another transaction in the set. Deadlock prevention protocols ensure that the system will neve r enter into a deadlock state. Some prevention strategies : Require that each transaction locks all its data items before it begins execution (predeclaration).
- 14. More Deadlock Prevention Strategies Following schemes use transaction timestamps for the sake of deadlo ck prevention alone. wait-die scheme — non-preemptive older transaction may wait for younger one to release data item. (o lder means smaller timestamp) Younger transactions never Young er transactions never wait for older ones; they are rolled back inst ead. a transaction may die several times before acquiring needed data item wound-wait scheme — preemptive older transaction wounds (forces rollback) of younger transaction i nstead of waiting for it. Younger transactions may wait for older on es. may be fewer rollbacks than wait-die scheme.
- 15. Deadlock prevention (Cont.) Both in wait-die and in wound-wait schemes, a rolled back transaction s is restarted with its original timestamp. Older transactions thus have precedence over newer ones, and starvation is hence avoided. Timeout-Based Schemes: a transaction waits for a lock only for a specified amount of time. If the lock has not been granted within that time, the transaction is ro lled back and restarted, Thus, deadlocks are not possible simple to implement; but starvation is possible. Also difficult to det ermine good value of the timeout interval.
- 16. Deadlock Detection Deadlocks can be described as a wait-for graph, which consists of a p air G = (V,E), V is a set of vertices (all the transactions in the system) E is a set of edges; each element is an ordered pair Ti Tj. If Ti Tj is in E, then there is a directed edge from Ti to Tj, implying th at Ti is waiting for Tj to release a data item. When Ti requests a data item currently being held by Tj, then the edge Ti Tj is inserted in the wait-for graph. This edge is removed only wh en Tj is no longer holding a data item needed by Ti. The system is in a deadlock state if and only if the wait-for graph has a cycle. Must invoke a deadlock-detection algorithm periodically to look for cycles.
- 17. Deadlock Detection (Cont.) Wait-for graph without a cycle Wait-for graph with a cycle
- 18. Deadlock Recovery When deadlock is detected : Some transaction will have to rolled back (made a victim) to bre ak deadlock. Select that transaction as victim that will incur min imum cost. Rollback -- determine how far to roll back transaction Total rollback: Abort the transaction and then restart it. More effective to roll back transaction only as far as necessa ry to break deadlock. Starvation happens if same transaction is always chosen as vict im. Include the number of rollbacks in the cost factor to avoid st arvation
- 19. Example of Granularity Hierarchy The levels, starting from the coarsest (top) level are database area file record
- 20. Timestamp-Based Protocols Each transaction is issued a timestamp when it enters the system. If a n old transaction Ti has time-stamp TS(Ti), a new transaction Tj is assi gned time-stamp TS(Tj) such that TS(Ti) <TS(Tj). The protocol manages concurrent execution such that the time-stamps determine the serializability order. In order to assure such behavior, the protocol 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.
- 21. Timestamp-Based Protocols (Cont.) The timestamp ordering protocol ensures that any conflicting read a nd write operations are executed in timestamp order. Suppose a transaction Ti issues a read(Q) 1. 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. 2. If TS(Ti) W-timestamp(Q), then the read operation is execute d, and R-timestamp(Q) is set to max(R-timestamp(Q), TS(Ti)).
- 22. Timestamp-Based Protocols (Cont.) Suppose that transaction Ti issues write(Q). 1. If TS(Ti) < R-timestamp(Q), then the value of Q that Ti is producin g was needed previously, and the system assumed that that valu e would never be produced. Hence, the write operation is rejected, and Ti is rolled back. 2. If TS(Ti) < W-timestamp(Q), then Ti is attempting to write an obsol ete value of Q. Hence, this write operation is rejected, and Ti is rolled back. 3. Otherwise, the write operation is executed, and W-timestamp(Q) is set to TS(Ti).
- 23. Example Use of the Protocol A partial schedule for several data items for transactions with timestamps 1, 2, 3, 4, 5
- 24. Thomas’ Write Rule Modified version of the timestamp-ordering protocol in which obsolete write operations may be ignored under certain circumstances. When Ti attempts to write data item Q, if TS(Ti) < W-timestamp(Q), the n Ti is attempting to write an obsolete value of {Q}. Rather than rolling back Ti as the timestamp ordering protocol wou ld have done, this {write} operation can be ignored. Otherwise this protocol is the same as the timestamp ordering protoco l. Thomas' Write Rule allows greater potential concurrency. Allows some view-serializable schedules that are not conflict-serial izable.
- 25. Validation-Based Protocol Execution of transaction Ti is done in three phases. 1. Read and execution phase: Transaction Ti writes only to temporary local variables 2. Validation phase: Transaction Ti performs a ''validation test'' to determine if local variables can be written without violating serializability. 3. Write phase: If Ti is validated, the updates are applied to the database; otherwise, Ti is rolled back. The three phases of concurrently executing transactions can be interlea ved, but each transaction must go through the three phases in that order. Assume for simplicity that the validation and write phase occur togeth er, atomically and serially I.e., only one transaction executes validation/write at a time. Also called as optimistic concurrency control since transaction execut es fully in the hope that all will go well during validation
- 26. Validation-Based Protocol (Cont.) Each transaction Ti has 3 timestamps Start(Ti) : the time when Ti started its execution Validation(Ti): the time when Ti entered its validation phase Finish(Ti) : the time when Ti finished its write phase Serializability order is determined by timestamp given at validation tim e; this is done to increase concurrency. Thus, TS(Ti) is given the value of Validation(Ti). This protocol is useful and gives greater degree of concurrency if prob ability of conflicts is low. because the serializability order is not pre-decided, and relatively few transactions will have to be rolled back.
- 27. Validation Test for Transaction Tj If for all Ti with TS (Ti) < TS (Tj) either one of the following condition holds: finish(Ti) < start(Tj) start(Tj) < finish(Ti) < validation(Tj) and the set of data items written by Ti does not intersect with the set of data items read by Tj. then validation succeeds and Tj can be committed. Otherwise, validation fails and Tj is aborted. Justification: Either the first condition is satisfied, and there is no o verlapped execution, or the second condition is satisfied and the writes of Tj do not affect reads of Ti since they occur after Ti has finished its reads. the writes of Ti do not affect reads of Tj since Tj does not read any item written by Ti.
- 28. Schedule Produced by Validation Example of schedule produced using validation
- 29. Deadlocks Consider the following two transactions: T1: write (X) T2: write(Y) write(Y) write(X) Schedule with deadlock
- 30. References Silberschatz A., Korth H., Sudarshan S., "Data base System Concepts", 6thEdition, McGraw Hill Publishers, ISBN 0-07-120413-X. Chapter 15