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A scalar function returns only one value (or NULL), whereas a table function returns a (relational) table comprising zero or more rows, each row with one or more columns. Functions must return a value (using the RETURN keyword), but for stored procedures this is not mandatory. Stored procedures can use RETURN keyword but with no value being passed.
An ORDER BY clause in SQL specifies that a SQL SELECT statement returns a result set with the rows being sorted by the values of one or more columns. The sort criteria does not have to be included in the result set (restrictions apply for SELECT DISTINCT, GROUP BY, UNION [DISTINCT], EXCEPT [DISTINCT] and INTERSECT [DISTINCT].)
SQL includes operators and functions for calculating values on stored values. SQL allows the use of expressions in the select list to project data, as in the following example, which returns a list of books that cost more than 100.00 with an additional sales_tax column containing a sales tax figure calculated at 6% of the price.
Multiple overlays can be used at once, forming a stack of modules between the frontend and the backend. Overlays provide a simple means to augment the functionality of a database without requiring that an entirely new backend be written, and allow new functionalities to be added in compact, easily debuggable and maintainable modules.
The return value from a function is provided within the function by making an assignment to an identifier with the same name as the function. [5] However, some versions of Pascal provide a special function Exit(exp); that can be used to return a value immediately from a function, or, without parameters, to return immediately from a procedure. [6]
Many-valued logic (also multi-or multiple-valued logic) is a propositional calculus in which there are more than two truth values. Traditionally, in Aristotle's logical calculus, there were only two possible values (i.e., "true" and "false") for any proposition. Classical two-valued logic may be extended to n-valued logic for n greater than 2.
By imputing multiple times, multiple imputation accounts for the uncertainty and range of values that the true value could have taken. As expected, the combination of both uncertainty estimation and deep learning for imputation is among the best strategies and has been used to model heterogeneous drug discovery data.