For years, database administrators and developers working with SQL Server faced a persistent performance issue known as parameter sniffing. This problem arises because SQL Server’s traditional query plan caching mechanism generates only a single execution plan for a parameterized query. That plan is based on the parameter values used during the query’s first execution. 

While efficient in many cases, this behavior leads to significant performance degradation when parameter values vary widely in terms of their data selectivity or distribution. For example, a plan optimized for a parameter value that filters a small subset of rows can be reused for a parameter that retrieves millions of rows, causing inefficient scans and resource overuse.