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The CASE expression, for example, enables SQL to perform conditional branching within queries, providing a mechanism to return different values based on evaluated conditions. This logic can be particularly useful for data transformation during retrieval, especially in SELECT statements.
The OFFSET clause specifies the number of rows to skip before starting to return data. The FETCH FIRST clause specifies the number of rows to return. Some SQL databases instead have non-standard alternatives, e.g. LIMIT, TOP or ROWNUM. The clauses of a query have a particular order of execution, [5] which is denoted by the number on the right ...
A condition is shown to affect a decision's outcome independently by varying just that condition while holding fixed all other possible conditions. The condition/decision criterion does not guarantee the coverage of all conditions in the module because in many test cases, some conditions of a decision are masked by the other conditions. Using ...
A multiset may be formally defined as an ordered pair (A, m) where A is the underlying set of the multiset, formed from its distinct elements, and : + is a function from A to the set of positive integers, giving the multiplicity – that is, the number of occurrences – of the element a in the multiset as the number m(a). (It is also possible ...
Set operations in SQL is a type of operations which allow the results of multiple queries to be combined into a single result set. [ 1 ] Set operators in SQL include UNION , INTERSECT , and EXCEPT , which mathematically correspond to the concepts of union , intersection and set difference .
SELECT * FROM (SELECT ROW_NUMBER OVER (ORDER BY sort_key ASC) AS row_number, columns FROM tablename) AS foo WHERE row_number <= 10 ROW_NUMBER can be non-deterministic : if sort_key is not unique, each time you run the query it is possible to get different row numbers assigned to any rows where sort_key is the same.
After the aggregating operation, HAVING is applied, filtering out the rows that don't match the specified conditions. Therefore, WHERE applies to data read from tables, and HAVING should only apply to aggregated data, which isn't known in the initial stage of a query. To view the present condition formed by the GROUP BY clause, the HAVING ...
(selects one of two values based on whether the two strings are equal—a numerical comparison is done whenever that is possible) {{#switch: test string | case1 = value for case 1 | ... | default}} (chooses between multiple alternatives based on the value of the test string—basically equivalent to a chain of #ifeq tests, but much more efficient)