When using set operators like UNION, INTERSECT, or EXCEPT (sometimes called MINUS) in relational database queries, the data sets being combined must have compatible structures. This compatibility necessitates an identical number of columns in each result set, and those columns must share comparable data types. If the result sets produced by the queries being combined by the set operator differ in their column counts, a structural mismatch occurs, leading to an error. For example, attempting to UNION the results of a query selecting two columns (e.g., name, age) with another selecting three columns (e.g., city, state, zip) will fail.
Maintaining consistent column counts across queries connected by set operators is fundamental to relational database integrity. It ensures meaningful data aggregation. Without this structural consistency, combining result sets becomes illogical, akin to adding apples and oranges. This principle underlies set theory and has been integral to database design since relational databases emerged in the 1970s. Enforcing structural compatibility safeguards data accuracy and prevents unintended results when using set operations, contributing to robust and reliable data management practices.
