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As we described earlier in this chapter, the familiar example is the act of moving money from a savings account to a checking account. The customer thinks of the act as a single action, but the database must take two actions. The database must reduce the balance in the savings account, and increase the balance in the checking account. If the first action should succeed, and the second fail (perhaps the computer fails at that instant), the customer will be very unhappy, for their savings account will contain less and their checking account will contain what it did. The customer would prefer that both actions be successful, but if the second action fails, the customer wants to be sure that everything will be put back as it was initially. Either every change must be successful, or no change must occur. Database management systems allow the user (or programmer) to specify transaction boundaries. Every change to the database that occurs within the transaction boundaries must be successful, or the transaction will be rolled back. When a transaction is rolled back, the values of all columns in all rows will be restored to the values they had when the transaction began. Transactions are implemented using write-ahead logging. Changes to the database, along with the previous values, are written to the log, not to the database, as the transaction proceeds. When the transaction is completely successful, it is committed. At that point the changes previously written to the log are actually written to the database, and the changes become visible to other users. On the other hand, if any part of the transaction fails, for any reason, the changes are rolled back, i.e., none of the changes written to the log are actually made to the database. Write-ahead logging is also useful in recovering a database from a system failure. The log contains all the changes to the database, including information about whether each transaction was committed or rolled back. To recover a database, the administrator can restore a previous backup of the database, and then process the transaction log, redoing committed transactions. This is called roll forward recovery. Some database systems use a write-ahead log, but also make changes to the database before the transaction is formally committed. In such a system, recovery from failure can be accomplished by restarting the DBMS and undoing transactions in the log that were not committed. This approach is called rollback recovery. TRANSACTION ISOLATION LEVELS When multiple users access a database simultaneously, there is a chance that one person s changes to the database will interfere with another person s work. For instance, suppose two people using an on-line flight reservation system both see that the window seat in row 18 is available, and both reserve it, nearly simultaneously. Without proper controls, both may believe they have successfully reserved the seat but, in fact, one will be disappointed. This is an example of one sort of concurrency problem, and it is called the lost update problem. The database literature describes desirable characteristics of transactions using the acronym ACID transactions should be atomic (all or nothing), consistent (all rows affected by the transaction are protected from other changes while the transaction is occurring), isolated (free from the effects of other activity in the database at the same time), and durable (permanent). The ideas of consistency and isolation are closely related. Besides the lost update problem, there are several other potential problems. For instance, dirty reads occur when one transaction reads uncommitted data provided by a second simultaneous transaction, which later rolls back the changes it made. Another problem is the nonrepeatable read, which occurs when a transaction has occasion to read the same data twice while accomplishing its work, only to find the data changed when it reads the data a second time. This can happen if another transaction makes a change to the data while the first is executing. A similar issue is the phantom read. If one transaction reads a set of records twice in the course of its work, it may find new records when it reads the database a second time. That could happen if a second transaction inserted a new record in the database in the meantime. The solutions to all these problems involve locking mechanisms to insure consistency and isolation of users and transactions. In the old days, programmers managed their own locks to provide the necessary protection, but today one usually relies on the DBMS to manage the locks. To prevent the lost update problem, the DBMS will manage read and write locks to insure lost updates do not occur. To address the other possible problems, one simply specifies the level of isolation required, using one of four levels standardized by the 1992 SQL standard. The reason the standard provides different levels of protection is that greater protection usually comes at the cost of reduced performance (less concurrency, and therefore fewer transactions per unit time).
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