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transactions, such as those that modify the structure of the database, or for complex queries that must sequentially scan many large tables. In these cases, it may be more efficient to rapidly do a single locking operation, quickly execute the database operation, and then quickly unlock the database, than to individually lock dozens of tables. An enhanced form of locking is table-level locking. In this scheme, the DBMS locks only the tables accessed by a transaction. Other transactions can concurrently access other tables. This technique permits more parallel processing, but can still lead to unacceptably slow performance in applications such as order entry, where many users must share access to the same table or tables. Many older DBMS products implement locking at the page level. In this scheme, the DBMS locks individual blocks of data (pages) from the disk as they are accessed by a transaction. Other transactions are prevented from accessing the locked pages but may access (and lock for themselves) other pages of data. Page sizes of 2KB, 4KB, and 16KB are commonly used. Since a large table will be spread out over hundreds or thousands of pages, two transactions trying to access two different rows of a table will usually be accessing two different pages, allowing the two transactions to proceed in parallel. However, tables with short rows increase the odds that individual rows needed by different transactions will happen to be in the same page. Over the last decade, most of the major commercial DBMS systems have moved beyond page-level locking to row-level locks. Row-level locking allows two concurrent transactions that access two different rows of a table to proceed in parallel, even if the two rows fall in the same disk block. While this may seem a remote possibility, it can be a real problem with small tables containing small records, such as the OFFICES table in the sample database. Row-level locking provides a high degree of parallel transaction execution. Unfortunately, keeping track of locks on variable-length pieces of the database (in other words, rows) rather than fixed-size pages is a much more complex task, so increased parallelism comes at the cost of more sophisticated locking logic and increased overhead. In fact, for certain transactions or applications, the overhead of row-level locking might be greater than the performance gains of permitting more parallel operation within the database. Some DBMS products address this situation by automatically promoting many individual row-level locks into a page-level or table-level lock when the number of row-level locks for a given transaction rises above a certain limit. It s not always the case that a more granular (smaller) level of lock implementation is better; the best scheme heavily depends on the specific transactions and the SQL operations that they contain. It s theoretically possible to move beyond row-level locking to locking at the individual data-item level. In theory, this would provide even more parallelism than row-level locks, because it would allow concurrent access to the same row by two different transactions, provided they were accessing different sets of columns. The overhead in managing item-level locking, however, has thus far outweighed its potential advantages. No commercial SQL DBMS uses item-level locking. In fact, locking is an area of considerable research in database technology, and the locking schemes used in commercial DBMS products are much more sophisticated than the fundamental scheme described here. The most straightforward of these advanced locking schemes, using shared and exclusive locks, is described in the next section.
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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: 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. 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. 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 DBMS or outside intervention,
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Transaction B Unlocked Shared lock Exclusive lock Unlocked Transaction A Shared lock Exclusive lock OK OK OK OK OK NO OK NO NO
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FIGURE 12-11
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