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accounts A and B that is, the sum A + B is preserved after the execution of both transactions Similarly, if the transactions are executed one at a time in the order T2 followed by T1 , then the corresponding execution sequence is that of Figure 154 Again, as expected, the sum A + B is preserved, and the nal values of accounts A and B are $850 and $2150, respectively The execution sequences just described are called schedules They represent the chronological order in which instructions are executed in the system Clearly, a schedule for a set of transactions must consist of all instructions of those transactions, and must preserve the order in which the instructions appear in each individual transaction For example, in transaction T1 , the instruction write(A) must appear before the instruction read(B), in any valid schedule In the following discussion, we shall refer to the rst execution sequence (T1 followed by T2 ) as schedule 1, and to the second execution sequence (T2 followed by T1 ) as schedule 2 These schedules are serial: Each serial schedule consists of a sequence of instructions from various transactions, where the instructions belonging to one single transaction appear together in that schedule Thus, for a set of n transactions, there exist n! different valid serial schedules When the database system executes several transactions concurrently, the corresponding schedule no longer needs to be serial If two transactions are running concurrently, the operating system may execute one transaction for a little while, then perform a context switch, execute the second transaction for some time, and then switch back to the rst transaction for some time, and so on With multiple transactions, the CPU time is shared among all the transactions Several execution sequences are possible, since the various instructions from both transactions may now be interleaved In general, it is not possible to predict exactly how many instructions of a transaction will be executed before the CPU switches to.

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T2 read(A) temp := A * 01 A := A temp write(A) read(B) B := B + temp write(B)

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read(A) A := A 50 write(A) read(B) B := B + 50 write(B) Figure 154 Schedule 2 a serial schedule in which T2 is followed by T1

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where is measured in webers (Wb) When the two inductors are brought into proximity, some ux will be induced in each inductor due to the ux of the other inductor That is, some ux will be induced due to the current owing in the other inductor The induced ux is given by i (t) = Mi j (t) Here we are saying that this is the induced ux in inductor i due to the current owing in inductor j We call the constant of proportionality M the mutual inductance The number of windings in one inductor multiplied by the mutual ux in the second inductor, divided by the current in the second inductor, de ne the mutual inductance That is, M= N1 m2 N2 m1 = i 2 (t) i 1 (t) (620)

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15

T1 read(A) A := A 50 write(A)

FIGURE 2-14

read(A) temp := A * 01 A := A temp write(A) read(B) B := B + 50 write(B) read(B) B := B + temp write(B) Figure 155 Schedule 3 a concurrent schedule equivalent to schedule 1

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When mutual inductance is present, we have to modify the equation relating voltage and current (612) Let inductor 1 have inductance L 1 , voltage v 1 (t) with a current i 1 (t) owing through it, and similarly for inductor 2 Then v 1 (t) = L 1 v 2 (t) = L 2 di 2 di 1 +M dt dt di 1 di 2 +M dt dt (621) (622)

another transaction Thus, the number of possible schedules for a set of n transactions is much larger than n! Returning to our previous example, suppose that the two transactions are executed concurrently One possible schedule appears in Figure 155 After this execution takes place, we arrive at the same state as the one in which the transactions are executed serially in the order T1 followed by T2 The sum A + B is indeed preserved Not all concurrent executions result in a correct state To illustrate, consider the schedule of Figure 156 After the execution of this schedule, we arrive at a state where the nal values of accounts A and B are $950 and $2100, respectively This nal state is an inconsistent state, since we have gained $50 in the process of the concurrent execution Indeed, the sum A + B is not preserved by the execution of the two transactions If control of concurrent execution is left entirely to the operating system, many possible schedules, including ones that leave the database in an inconsistent state, such as the one just described, are possible It is the job of the database system to ensure that any schedule that gets executed will leave the database in a consistent state The concurrency-control component of the database system carries out this task We can ensure consistency of the database under concurrent execution by making sure that any schedule that executed has the same effect as a schedule that could have occurred without any concurrent execution That is, the schedule should, in some sense, be equivalent to a serial schedule We examine this idea in Section 155

The database system must control concurrent execution of transactions, to ensure that the database state remains consistent Before we examine how the database

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