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In SELECT statements SQL returns only results for which the WHERE clause returns a value of True; i.e., it excludes results with values of False and also excludes those whose value is Unknown. Along with True and False, the Unknown resulting from direct comparisons with Null thus brings a fragment of three-valued logic to SQL.
Major DBMSs, including SQLite, [5] MySQL, [6] Oracle, [7] IBM Db2, [8] Microsoft SQL Server [9] and PostgreSQL [10] support prepared statements. Prepared statements are normally executed through a non-SQL binary protocol for efficiency and protection from SQL injection, but with some DBMSs such as MySQL prepared statements are also available using a SQL syntax for debugging purposes.
Referential integrity is a property of data stating that all its references are valid. In the context of relational databases, it requires that if a value of one attribute (column) of a relation (table) references a value of another attribute (either in the same or a different relation), then the referenced value must exist. [1]
A SELECT statement retrieves zero or more rows from one or more database tables or database views. In most applications, SELECT is the most commonly used data manipulation language (DML) command. As SQL is a declarative programming language, SELECT queries specify a result set, but do not specify how to calculate it.
(This problem exists for both named and positional parameters.) But {{{1|}}} will evaluate to the empty string (a false value) because the vertical bar or pipe character, "|" , immediately following the parameter name specifies a default value (here an empty string because there is nothing between the pipe and the first closing curly brace) as ...
The MySQL database supports prepared statements. A prepared statement or a parameterized statement is used to execute the same statement repeatedly with high efficiency. Basic workflow. The prepared statement execution consists of two stages: prepare and execute. At the prepare stage a statement template is sent to the database server.
Databases and other data stores which treat the integrity of data as paramount often include the ability to handle transactions to maintain the integrity of data. A single transaction consists of one or more independent units of work, each reading and/or writing information to a database or other data store.
Data validation is intended to provide certain well-defined guarantees for fitness and consistency of data in an application or automated system. Data validation rules can be defined and designed using various methodologies, and be deployed in various contexts. [1]