A relational database management system uses SQL conditions or expressions in clauses and in clauses to subsets of data.
EXISTS[1] to determine whether rows exist in a subquery result.[2]To one row of data from a table called tab with a primary key column (pk) set to 100 - use the condition pk = 100:
To identify whether a table tab has rows of data with a duplicated column dk - use the condition having count(*) > 1:
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. This logic can be particularly useful for data transformation during retrieval, especially in SELECT statements. Meanwhile, COALESCE simplifies the process of handling NULL values by returning the first non-NULL value in a given list of expressions, which is especially useful in scenarios where data might be incomplete or missing. Furthermore, SQL's support for three-valued logic (True, False, Unknown) introduces nuances when handling NULL values in conditions, making it essential to carefully structure queries to account for the "Unknown" state that arises in certain comparisons with NULL values. Proper use of these advanced conditions enhances the flexibility and robustness of SQL queries, particularly in complex data retrieval and reporting environments.