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Rules for shared and exclusive locks
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Transaction A ORDERS unlocked
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DBMS OFFICES unlocked PRODUCTS unlocked
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Transaction B
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12:01 UPDATE ORDERS
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Exclusive lock for A
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Exclusive lock for B Shared lock for A
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12:02 UPDATE PRODUCT
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12:03 SELECT... FROM OFFICES
12:04 OK SELECT ... FROM OFFICES
Shared lock for A, B
PART III
12:05 UPDATE ORDERS
Shared lock for A Exclusive lock for A
12:05 Unlocked OK COMMIT
12:06 UPDATE OFFICES
12:07 COMMIT OK Unlocked Unlocked
FIGURE 12-12
Locking with shared and exclusive locks
each program will wait forever for the other program to commit or roll back its transaction, unlocking the data. The situation in the figure is a simple deadlock between two programs, but more complex situations can occur where three, four, or 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 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 error code informing it that it has lost a deadlock and that its current transaction has been rolled back.
Part III:
Updating Data
Transaction A ORDERS unlocked
DBMS PRODUCTS unlocked
Transaction B
12:01 UPDATE ORDERS
Exclusive lock for A Exclusive lock for B OK 12:02 UPDATE PRODUCT
12:03 UPDATE PRODUCT
WAIT
WAIT
12:04 UPDATE ORDERS
FIGURE 12-13
A transaction deadlock
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
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Tr a n s a c t i o n P r o c e s s i n g
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.
Advanced Locking Techniques*
Many commercial database products offer advanced locking facilities that go well beyond those provided by standard SQL transactions. These include Explicit locking A program can explicitly lock an entire table or some other part of the database if it will be repeatedly accessed by the program. Isolation levels You can tell the DBMS that a specific program will not re retrieve data during a transaction, allowing the DBMS to release locks before the transaction ends. Locking parameters The database administrator can manually adjust the size of the lockable piece of the database and other locking parameters to tune locking performance. These facilities tend to be nonstandard and product-specific. However, several of them, particularly those initially introduced in mainframe versions of DB2 years ago, have been implemented in several commercial SQL products and have achieved the status of common, if not standard, features. In fact, the isolation-level capabilities introduced in DB2 have found their way into the SQL standard.
PART III
Explicit Locking*
If a transaction repeatedly accesses a table, the overhead of acquiring small locks on many parts of the table can be very substantial. A bulk update program that walks through every row of a table, for example, will lock the entire table, piece by piece, as it proceeds. For this type of transaction, the program should explicitly lock the entire table, process the updates, and then unlock the table. Locking the entire table has three advantages: It eliminates the overhead of row-by-row (or page-by-page) locking. It eliminates the possibility that another transaction will lock part of the table, forcing the bulk update transaction to wait. It eliminates the possibility that another transaction will lock part of the table and deadlock the bulk update transaction, forcing it to be restarted. Of course, locking the table has the disadvantage that all other transactions attempting to access the table must wait while the update is in process. However, because the bulk update transaction can proceed much more quickly, the overall throughput of the DBMS can be increased by explicitly locking the table.
Part III:
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