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Record locking is the technique of preventing simultaneous access to data in a database, to prevent inconsistent results.. The classic example is demonstrated by two bank clerks attempting to update the same bank account for two different transactions.
To reduce contention for table blocks due to delete, select or update statements, reduce the number of rows per block. This can be done by using a smaller block size. To reduce contention for table blocks due to insert statements, increase the number of freelists, or buffer frames.
An SQL UPDATE statement changes the data of one or more records in a table. Either all the rows can be updated, or a subset may be chosen using a condition. The UPDATE statement has the following form: [1] UPDATE table_name SET column_name = value [, column_name = value ...] [WHERE condition]
For others, the application can implement an OCC layer outside of the database, and avoid waiting or silently overwriting records. In such cases, the form may include a hidden field with the record's original content, a timestamp, a sequence number, or an opaque token. On submit, this is compared against the database.
The CAP theorem is based on three trade-offs, one of which is "atomic consistency" (shortened to "consistency" for the acronym), about which the authors note, "Discussing atomic consistency is somewhat different than talking about an ACID database, as database consistency refers to transactions, while atomic consistency refers only to a property of a single request/response operation sequence.
Isolation is typically enforced at the database level. However, various client-side systems can also be used. It can be controlled in application frameworks or runtime containers such as J2EE Entity Beans [2] On older systems, it may be implemented systemically (by the application developers), for example through the use of temporary tables.
In database systems, durability is the ACID property that guarantees that the effects of transactions that have been committed will survive permanently, even in cases of failures, [1] including incidents and catastrophic events.
Some database implementations adopted the term upsert (a portmanteau of update and insert) to a database statement, or combination of statements, that inserts a record to a table in a database if the record does not exist or, if the record already exists, updates the existing record.