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As the three multiuser update examples show, when users share access to a database and one or more users is updating data, there is a potential for database corruption.
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SQL uses its transaction mechanism to eliminate this source of database corruption. In addition to the all-or-nothing commitment for the statements in a transaction, a SQL-based DBMS makes this commitment about transactions: During a transaction, the user will see a completely consistent view of the database. The user will never see the uncommitted changes of other users, and even committed changes made by others will not affect data seen by the user in mid-transaction.
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Transactions are thus the key to both recovery and concurrency control in a SQL database. The previous commitment can be restated explicitly in terms of concurrent transaction execution: If two transactions, A and B, are executing concurrently, the DBMS ensures that the results will be the same as they would be if either (a) Transaction A were executed first, followed by Transaction B, or (b) Transaction B were executed first, followed by Transaction A. This concept is known as the serializability of transactions. Effectively, it means that each database user can access the database as if no other users were concurrently accessing the database. In practice, dozens or hundreds of transactions may be concurrently executing within a large production database. The serializability concept can be directly extended to cover this situation. Serializability guarantees that, if some number, N, concurrent transactions are executing, the DBMS must ensure that its results are the same as if they had been executed in some sequence, one at a time. The concept does not specify which sequence of transactions must be used, only that the results must match the results of some sequence. The fact that a DBMS insulates you from the actions of other concurrent users doesn t mean, however, that you can forget all about the other users. In fact, the situation is quite the opposite. Because other users want to concurrently update the database, you should keep your transactions as short and simple as possible, to maximize the amount of parallel processing that can occur. Suppose, for example, that you run a program that performs a sequence of three large queries. Since the program doesn t update the database, it might seem that it doesn t need to worry about transactions. It certainly seems unnecessary to use COMMIT statements. But in fact, the program should use a COMMIT statement after each query. Why Recall that SQL automatically begins a transaction with the first SQL statement in a program. Without a COMMIT statement, the transaction continues until the program ends. Further, SQL guarantees that the data retrieved during a transaction will be self-consistent, unaffected by other users transactions. This means that once your program retrieves a row from the database, no other user can modify the row until your transaction ends, because you might try to retrieve the row again later in your transaction, and the DBMS must guarantee that you will see the same data. Thus, as your program performs its three queries, it will prevent other users from updating larger and larger portions of the database. The moral of this example is simple: you must always worry about transactions when writing programs for a production SQL database. Transactions should always be as short as possible COMMIT early and COMMIT often is good advice when you are using programmatic SQL. In practice, implementing a strict multiuser transaction model can impose a substantial overhead on the operation of a database with dozens, hundreds, or thousands of concurrent users. In addition, the specifics of the application may not require the absolute isolation among the user programs that the SQL transaction model implies. For example, maybe the application designer knows that an order inquiry
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