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The Ingres default is shared locking, which parallels the repeatable read default in the IBM scheme. Note, however, that the Ingres locking modes are set by an executable SQL statement. Unlike the IBM modes, which must be chosen at compile time, the Ingres modes can be chosen when the program executes and can even be changed from one query to the next.
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A mature DBMS such as DB2, SQL/DS, Oracle, Sybase ASE, or SQL Server employs much more complex locking techniques than those described here. The database administrator can improve the performance of these systems by manually setting the locking parameters. On the other hand, the vendors of current major DBMS products typically discourage attempts to control locking manually because things have become so complex that seemingly simple changes can make things worse instead of better. Older systems, however, might benefit from some tuning. Typical parameters that can be tuned include these: Lock size Some DBMS products offer a choice of table-level, page-level, row-level, and other lock sizes. Depending on the specific application, a different size lock may be appropriate. Number of locks A DBMS typically allows each transaction to have some finite number of locks. The database administrator can often set this limit, raising it to permit more complex transactions, or lowering it to encourage earlier lock escalation. Lock escalation A DBMS will often automatically escalate locks, replacing many small locks with a single larger lock (for example, replacing many page-level locks with a table-level lock). The database administrator may have some control over this escalation process. Lock timeout Even when a transaction is not deadlocked with another transaction, it may wait a very long time for the other transaction to release its locks. Some DBMS brands implement a timeout feature, where a SQL statement fails with a SQL error code if it cannot obtain the locks it needs within a certain period. The timeout period can usually be set by the database administrator.
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The locking techniques described in the preceding sections are the most widely used techniques for supporting concurrent multiuser transaction processing in relational DBMS products. Locking is sometimes called a pessimistic approach to concurrency, because by locking parts of the database, the DBMS is implicitly assuming that concurrent transactions will probably interfere with one another. In recent years, a different approach to concurrency, called versioning, has been implemented in some DBMS products and has been increasing in popularity. Versioning is sometimes called an optimistic approach to concurrency because in this approach, the DBMS implicitly assumes that concurrent transactions will not interfere with one another. With a locking (pessimistic) architecture, the DBMS internally maintains one and only one copy of the data for each row in the database. As multiple users access the database, the locking scheme arbitrates the access to this row of data among the users (more precisely, among their concurrent transactions). In contrast, with a versioning (optimistic) architecture,
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the DBMS will create two or more copies of the data for a row in the database when a user attempts to update the row. One copy of the row will contain the old data for the row, before the update; the other copy of the row will contain the new data for the row, after the update. The DBMS internally keeps track of which transactions should see which version of the row, depending on their isolation levels.
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Figure 12-16 shows a simple versioning architecture in action. Transaction A starts the action, reading a row of the PRODUCTS table, and finding 139 units of ACI-41004 size 4 widgets available. Transaction B comes along next and updates the same row, reducing the quantity
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