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In addition to basic equality and inequality conditions, SQL allows for more complex conditional logic through constructs such as CASE, COALESCE, and NULLIF.The CASE expression, for example, enables SQL to perform conditional branching within queries, providing a mechanism to return different values based on evaluated conditions.
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.
The relational algebra uses set union, set difference, and Cartesian product from set theory, and adds additional constraints to these operators to create new ones.. For set union and set difference, the two relations involved must be union-compatible—that is, the two relations must have the same set of attributes.
To give an example, imagine a relational database for storing information about students, their address, the courses they take and their gender. Finding all male students and their addresses who attend a course that is also attended by a female student is expressed by the following conjunctive query: (student, address) . ∃ (student2, course) .
The following example EXCEPT query returns all rows from the Orders table where Quantity is between 1 and 49, and those with a Quantity between 76 and 100. Worded another way; the query returns all rows where the Quantity is between 1 and 100, apart from rows where the quantity is between 50 and 75.
all rows for which the predicate in the WHERE clause is True are affected (or returned) by the SQL DML statement or query. Rows for which the predicate evaluates to False or Unknown are unaffected by the DML statement or query. The following query returns only those rows from table mytable where the value in column mycol is greater than 100.
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.
Columnar storage also allows fast execution of range queries (e.g., show all records where a particular column is between X and Y, or less than X.) In all these cases, however, the database designer does not have to perform 6NF normalization manually by creating separate tables.