Course Database Management Systems - Chapter 5: Concurrency Control Techniques - Nguyen Thanh Tung

Nội dung text: Course Database Management Systems - Chapter 5: Concurrency Control Techniques - Nguyen Thanh Tung

1. Outline Databases Concurrency Control 1 Purpose of Concurrency Control 2 Two-Phase locking 3 Concurrency control based on Timestamp ordering 4 Multiversion Concurrency Control techniques 5 Lock Compatibility Matrix 6 Lock Granularity 2
2. Database Concurrency Control Two-Phase Locking Techniques Locking is an operation which secures (a) permission to Read or (b) permission to Write a data item for a transaction. Example: Lock(X). Data item X is locked in behalf of the requesting transaction. Unlocking is an operation which removes these permissions from the data item. Example: Unlock(X). Data item X is made available to all other transactions. Lock and Unlock are atomic operations. 4
3. Database Concurrency Control Two-Phase Locking Techniques: Essential components Lock Manager: Managing locks on data items. Lock table: Lock manager uses it to store the identity of transaction locking (the data item, lock mode and pointer to the next data item locked). One simple way to implement a lock table is through linked list. Transaction ID Data item id lock mode Ptr to next data item T1 X1 Read Next 6
4. Database Concurrency Control Two-Phase Locking Techniques: Essential components The following code performs the lock operation: B: if LOCK (X) = 0 (*item is unlocked*) then LOCK (X)  1 (*lock the item*) else begin wait (until lock (X) = 0 and the lock manager wakes up the transaction); goto B end; 8
5. Database Concurrency Control Two-Phase Locking Techniques: Essential components The following code performs the read lock operation: B: if LOCK (X) = “unlocked” then begin LOCK (X)  “read-locked”; no_of_reads (X)  1; end else if LOCK (X)  “read-locked” then no_of_reads (X)  no_of_reads (X) +1 else begin wait (until LOCK (X) = “unlocked” and the lock manager wakes up the transaction); go to B end; 10
6. Database Concurrency Control Two-Phase Locking Techniques: Essential components The following code performs the unlock operation: if LOCK (X) = “write-locked” then begin LOCK (X)  “unlocked”; wakes up one of the transactions, if any end else if LOCK (X)  “read-locked” then begin no_of_reads (X)  no_of_reads (X) -1 if no_of_reads (X) = 0 then begin LOCK (X) = “unlocked”; wake up one of the transactions, if any end end; 12
7. Database Concurrency Control Two-Phase Locking Techniques: Essential components Lock conversion Lock upgrade: existing read lock to write lock if Ti has a read-lock (X) and Tj has no read-lock (X) (i j) then convert read-lock (X) to write-lock (X) else force Ti to wait until Tj unlocks X Lock downgrade: existing write lock to read lock Ti has a write-lock (X) (*no transaction can have any lock on X*) convert write-lock (X) to read-lock (X) 14
8. Database Concurrency Control Two-Phase Locking Techniques: The algorithm T1 T2 Result read_lock (Y); read_lock (X); Initial values: X=20; Y=30 read_item (Y); read_item (X); Result of serial execution unlock (Y); unlock (X); T1 followed by T2 write_lock (X); Write_lock (Y); X=50, Y=80. read_item (X); read_item (Y); Result of serial execution X:=X+Y; Y:=X+Y; T2 followed by T1 write_item (X); write_item (Y); X=70, Y=50 unlock (X); unlock (Y); 16
9. Database Concurrency Control Two-Phase Locking Techniques: The algorithm T’1 T’2 read_lock (Y); read_lock (X); T1 and T2 follow two-phase read_item (Y); read_item (X); policy but they are subject to write_lock (X); write_lock (Y); deadlock, which must be unlock (Y); unlock (X); dealt with. read_item (X); read_item (Y); X:=X+Y; Y:=X+Y; write_item (X); write_item (Y); unlock (X); unlock (Y); 18
10. Database Concurrency Control Dealing with Deadlock and Starvation Deadlock T’1 T’2 read_lock (Y); T’1 and T’2 did follow two-phase read_item (Y); policy but they are deadlock read_lock (X); read_item (X); write_lock (X); (waits for X) write_lock (Y); (waits for Y) Deadlock (T’1 and T’2) 20
11. Database Concurrency Control Dealing with Deadlock and Starvation Deadlock detection and resolution In this approach, deadlocks are allowed to happen. The scheduler maintains a wait-for-graph for detecting cycle. If a cycle exists, then one transaction involved in the cycle is selected (victim) and rolled-back. A wait-for-graph is created using the lock table. As soon as a transaction is blocked, it is added to the graph. When a chain like: Ti waits for Tj waits for Tk waits for Ti or Tj occurs, then this creates a cycle. One of the transactions of the cycle is selected and rolled back. 22
12. Database Concurrency Control Dealing with Deadlock and Starvation Deadlock avoidance There are many variations of two-phase locking algorithm. Some avoid deadlock by not letting the cycle to complete. That is as soon as the algorithm discovers that blocking a transaction is likely to create a cycle, it rolls back the transaction. Wound-Wait and Wait-Die algorithms use timestamps to avoid deadlocks by rolling-back victim. 24
13. Database Concurrency Control Timestamp based concurrency control algorithm Timestamp A monotonically increasing variable (integer) indicating the age of an operation or a transaction. A larger timestamp value indicates a more recent event or operation. Timestamp-based algorithm uses timestamp to serialize the execution of concurrent transactions. 26
14. Database Concurrency Control Timestamp based concurrency control algorithm Basic Timestamp Ordering 1. Transaction T issues a write_item(X) operation: a. If read_TS(X) > TS(T) or if write_TS(X) > TS(T), then an younger transaction has already read the data item so abort and roll-back T and reject the operation. b. If the condition in part (a) does not exist, then execute write_item(X) of T and set write_TS(X) to TS(T). 2. Transaction T issues a read_item(X) operation: a. If write_TS(X) > TS(T), then an younger transaction has already written to the data item so abort and roll- back T and reject the operation. b. If write_TS(X) TS(T), then execute read_item(X) of T and set read_TS(X) to the larger of TS(T) and the current read_TS(X). 28
15. Database Concurrency Control Timestamp based concurrency control algorithm Strict Timestamp Ordering 1. Transaction T issues a write_item(X) operation: a. If TS(T) > write_TS(X), then delay T until the transaction T’ that wrote X has terminated (committed or aborted). 2. Transaction T issues a read_item(X) operation: a. If TS(T) > write_TS(X), then delay T until the transaction T’ that wrote X has terminated (committed or aborted). 30
16. Database Concurrency Control Multiversion concurrency control techniques Concept This approach maintains a number of versions of a data item and allocates the right version to a read operation of a transaction. Thus unlike other mechanisms a read operation in this mechanism is never rejected. Side effect: Significantly more storage (RAM and disk) is required to maintain multiple versions. To check unlimited growth of versions, a garbage collection is run when some criteria are satisfied. 32
17. Database Concurrency Control Multiversion technique based on timestamp ordering To ensure serializability, the following two rules are used. If transaction T issues write_item(X) and version i of X has the highest write_TS(Xi) of all versions of X that is also less than or equal to TS(T), and read _TS(Xi) > TS(T), then abort and roll-back T; otherwise create a new version Xj and read_TS(Xj) = write_TS(Xj) = TS(T). If transaction T issues read_item (X), find the version i of X that has the highest write_TS(Xi) of all versions of X that is also less than or equal to TS(T), then return the value of Xi to T, and set the value of read _TS(Xi) to the largest of TS(T) and the current read_TS(Xi). Rule 2 guarantees that a read will never be rejected. 34
18. Database Concurrency Control Multiversion Two-Phase Locking Using Certify Locks Concept Allow a transaction T’ to read a data item X while it is write- locked by a conflicting transaction T. This is accomplished by maintaining two versions of each data item X where one version must always have been written by some committed transaction. This means a write operation always creates a new version of X. 36
19. Database Concurrency Control Multiversion Two-Phase Locking Using Certify Locks Note In multiversion 2PL, read and write operations from conflicting transactions can be processed concurrently. This improves concurrency but it may delay transaction commit because of obtaining certify locks on all its writes. It avoids cascading abort but like strict two-phase locking scheme, conflicting transactions may get deadlocked if upgrading of a read lock to a write lock is allowed. 38
20. Database Concurrency Control Validation (Optimistic) Concurrency Control Schemes Validation phase: Serializability is checked before transactions write their updates to the database. This phase for Ti checks that, for each transaction Tj that is either committed or is in its validation phase, one of the following conditions holds: 1. Tj completes its write phase before Ti starts its read phase. 2. Ti starts its write phase after Tj completes its write phase, and the read_set of Ti has no items in common with the write_set of Tj 3. Both the read_set and write_set of Ti have no items in common with the write_set of Tj, and Tj completes its read phase before Ti completes its read phase. 40
21. Database Concurrency Control Granularity of data items and Multiple Granularity Locking A lockable unit of data defines its granularity. Granularity can be coarse (entire database) or it can be fine (a tuple or an attribute of a relation). Data item granularity significantly affects concurrency control performance. Thus, the degree of concurrency is low for coarse granularity and high for fine granularity. Example of data item granularity: 1. A field of a database record (an attribute of a tuple). 2. A database record (a tuple or a relation). 3. A disk block. 4. An entire file. 5. The entire database. 42
22. Database Concurrency Control Granularity of data items and Multiple Granularity Locking To manage such hierarchy, in addition to read and write, three additional locking modes, called intention lock modes are defined: Intention-shared (IS): indicates that a shared lock(s) will be requested on some descendent nodes(s). Intention-exclusive (IX): indicates that an exclusive lock(s) will be requested on some descendent nodes(s). Shared-intention-exclusive (SIX): indicates that the current node is locked in shared mode but an exclusive lock(s) will be requested on some descendent nodes(s). 44
23. Database Concurrency Control Granularity of data items and Multiple Granularity Locking The set of rules which must be followed for producing serializable schedule are 1. The lock compatibility must adhered to. 2. The root of the tree must be locked first, in any mode. 3. A node N can be locked by a transaction T in S or IX mode only if the parent node is already locked by T in either IS or IX mode. 4. A node N can be locked by T in X, IX, or SIX mode only if the parent of N is already locked by T in either IX or SIX mode. 5. T can lock a node only if it has not unlocked any node (to enforce 2PL policy). 6. T can unlock a node, N, only if none of the children of N are currently locked by T. 46
24. Database Concurrency Control Granularity of data items and Multiple Granularity Locking An example of a serializable execution (continued): T1 T2 T3 unlock(p12) unlock(f1) unlock(db) unlock(r111) unlock(p11) unlock(f1) unlock(db) unlock (r11j) unlock (p11) unlock (f1) unlock(f2) unlock(db) 48