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To increase concurrent access to a database, most commercial DBMS products use a locking scheme with more than one type of lock. A scheme using shared and exclusive locks is quite common: I Shared lock. Used by the DBMS when a transaction wants to read data from the database. Another concurrent transaction can also acquire a shared lock on the same data, allowing the other transaction to also read the data. I Exclusive lock. Used by the DBMS when a transaction wants to update data in the database. When a transaction has an exclusive lock on some data, other transactions cannot acquire any type of lock (shared or exclusive) on the data. Figure 12-11 shows the rules for this locking scheme and the permitted combinations of locks that can be held by two concurrent transactions. Note that a transaction can acquire an exclusive lock only if no other transaction currently has a shared or an exclusive lock on the data. If a transaction tries to acquire a lock not permitted by the rules in Figure 12-11, it is blocked until other transactions unlock the data that it requires. Figure 12-12 shows the same transactions shown in Figure 12-10, this time using shared and exclusive locks. If you compare the two figures, you can see how the new locking scheme improves concurrent access to the database. Mature and complex DBMS products, such as DB2, have more than two types of locks and use different locking techniques at different levels of the database. Despite the increased complexity, the goal of the locking scheme remains the same: to prevent unwanted interference between transactions while providing the greatest possible concurrent access to the database, all with minimal locking overhead.
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Unfortunately, the use of any locking scheme to support concurrent SQL transactions leads to a problem called a deadlock. Figure 12-13 illustrates a deadlock situation.
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Figure 12-11.
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Figure 12-12.
Locking with shared and exclusive locks
Program A updates the ORDERS table, thereby locking part of it. Meanwhile, Program B updates the PRODUCTS table, locking part of it. Now Program A tries to update the PRODUCTS table and Program B tries to update the ORDERS table, in each case trying to update a part of the table that has been previously locked by the other program (the same row or the same page, depending on the type of locking implemented). Without outside intervention, each program will wait forever for the other program to commit its transaction and unlock the data. The situation in the figure is a simple deadlock between two programs, but more complex situations can occur where three, four, or
SQL: The Complete Reference
Figure 12-13.
A transaction deadlock
more programs are in a cycle of locks, each waiting for data that is locked by one of the other programs. To deal with deadlocks, a DBMS typically includes logic that periodically (for example, once every five seconds) checks the locks held by various transactions. When it detects a deadlock, the DBMS arbitrarily chooses one of the transactions as the deadlock loser and rolls back the transaction. This frees the locks held by the losing transaction, allowing the deadlock winner to proceed. The losing program receives an
12:
Transaction Processing
error code informing it that it has lost a deadlock and that its current transaction has been rolled back. This scheme for breaking deadlocks means that any SQL statement can potentially return a deadlock loser error code, even if nothing is wrong with the statement per se. Thus, even though COMMIT and ROLLBACK are the SQL transaction-processing statements, it s possible for other SQL statements an INSERT statement, for example, or even a SELECT statement to be a deadlock loser. The transaction attempting the statement is rolled back through no fault of its own, but because of other concurrent activity in the database. This may seem unfair, but in practice, it s much better than the other two alternatives eternal deadlock or database corruption. If a deadlock loser error occurs in interactive SQL, the user can simply retype the SQL statement(s). In programmatic SQL, the application program must be prepared to handle the deadlock loser error code. Typically, the program will respond by either alerting the user or automatically retrying the transaction. The probability of deadlocks can be dramatically reduced by carefully planning database updates. All programs that update multiple tables during a transaction should, whenever possible, update the tables in the same sequence. This allows the locks to flow smoothly across the tables, minimizing the possibility of deadlocks. In addition, some of the advanced locking features described in later sections of this chapter can be used to further reduce the number of deadlocks that occur.
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