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2452 Concurrency Control
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The fundamental goal of database concurrency control is to ensure that concurrent execution of transactions does not result in a loss of database consistency The concept of serializability can be used to achieve this goal, since all serializable schedules preserve consistency of the database However, not all schedules that preserve consistency of the database are serializable For an example, consider again a bank database consisting of two accounts A and B, with the consistency requirement that the sum A + B be preserved Although the schedule of Figure 245 is not con ict serializable, it nevertheless preserves the sum of A + B It also illustrates two important points about the concept of correctness without serializability Correctness depends on the speci c consistency constraints for the database Correctness depends on the properties of operations performed by each transaction In general it is not possible to perform an automatic analysis of low-level operations by transactions and check their effect on database consistency constraints However, there are simpler techniques One is to use the database consistency constraints as
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Silberschatz Korth Sudarshan: Database System Concepts, Fourth Edition
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VII Other Topics
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24 Advanced Transaction Processing
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Long-Duration Transactions
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T1 read(A) A := A 50 write(A)
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read(B) B := B 10 write(B) read(B) B := B + 50 write(B) read(A) A := A + 10 write(A) Figure 245 A non-con ict-serializable schedule
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the basis for a split of the database into subdatabases on which concurrency can be managed separately Another is to treat some operations besides read and write as fundamental low-level operations, and to extend concurrency control to deal with them The bibliographical notes reference other techniques for ensuring consistency without requiring serializability Many of these techniques exploit variants of multiversion concurrency control (see Section 176) For older data-processing applications that need only one version, multiversion protocols impose a high space overhead to store the extra versions Since many of the new database applications require the maintenance of versions of data, concurrency-control techniques that exploit multiple versions are practical
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2453 Nested and Multilevel Transactions
A long-duration transaction can be viewed as a collection of related subtasks or subtransactions By structuring a transaction as a set of subtransactions, we are able to enhance parallelism, since it may be possible to run several subtransactions in parallel Furthermore, it is possible to deal with failure of a subtransaction (due to abort, system crash, and so on) without having to roll back the entire long-duration transaction A nested or multilevel transaction T consists of a set T = {t1 , t2 , , tn } of subtransactions and a partial order P on T A subtransaction ti in T may abort without forcing T to abort Instead, T may either restart ti or simply choose not to run ti If ti commits, this action does not make ti permanent (unlike the situation in 17) Instead, ti commits to T, and may still abort (or require compensation see Section 2454) if T aborts An execution of T must not violate the partial order P That is, if an edge ti tj appears in the precedence graph, then tj ti must not be in the transitive closure of P
Silberschatz Korth Sudarshan: Database System Concepts, Fourth Edition
VII Other Topics
24 Advanced Transaction Processing
The McGraw Hill Companies, 2001
24
Advanced Transaction Processing
Nesting may be several levels deep, representing a subdivision of a transaction into subtasks, subsubtasks, and so on At the lowest level of nesting, we have the standard database operations read and write that we have used previously If a subtransaction of T is permitted to release locks on completion, T is called a multilevel transaction When a multilevel transaction represents a long-duration activity, the transaction is sometimes referred to as a saga Alternatively, if locks held by a subtransaction ti of T are automatically assigned to T on completion of ti , T is called a nested transaction Although the main practical value of multilevel transactions arises in complex, long-duration transactions, we shall use the simple example of Figure 245 to show how nesting can create higher-level operations that may enhance concurrency We rewrite transaction T1 , using subtransactions T1,1 and T1,2 , which perform increment or decrement operations: T1 consists of T1,1 , which subtracts 50 from A T1,2 , which adds 50 to B Similarly, we rewrite transaction T2 , using subtransactions T2,1 and T2,2 , which also perform increment or decrement operations: T2 consists of T2,1 , which subtracts 10 from B T2,2 , which adds 10 to A No ordering is speci ed on T1,1 , T1,2 , T2,1 , and T2,2 Any execution of these subtransactions will generate a correct result The schedule of Figure 245 corresponds to the schedule < T1,1 , T2,1 , T1,2 , T2,2 >
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