Introduction

Have you ever noticed that when you view query plans in SQL Server Management Studio (SSMS), scalar user-defined functions (UDFs) appear in the estimated plan but mysteriously vanish from the actual plan? In this article, we’ll explore the reasons behind this behavior and discuss its implications for query optimization and performance.

Understanding Scalar UDFs

Scalar UDFs are T-SQL functions that return a single value. They can be used to encapsulate complex logic or calculations and promote code reusability. However, scalar UDFs have a reputation for negatively impacting query performance due to their inherent limitations.

Estimated vs. Actual Query Plans

When you execute a query in SSMS, two types of query plans are generated:

1. Estimated Plan: Created by the query optimizer before executing the query, based on statistics and heuristics.
2. Actual Plan: Shows the real execution path taken by the query engine after running the query.

The discrepancy between estimated and actual plans for scalar UDFs lies in how they are treated by the query optimizer.

Scalar UDFs in Estimated Plans

In estimated plans, scalar UDFs appear as separate operators, indicating that the optimizer considers them as distinct units of work. The optimizer estimates the cost of executing the UDF based on generic statistics, without knowing the actual runtime behavior.

Example:

SELECT dbo.CalculateDiscount(Price) AS DiscountedPrice
FROM Products;

In the estimated plan, you’ll see the CalculateDiscount UDF represented as a separate operator.

Disappearance from Actual Plans

However, when you view the actual execution plan, the scalar UDF seemingly disappears. This is because the query engine inlines the scalar UDF code directly into the calling query during execution. Inlining means that the UDF’s code is integrated into the main query, eliminating the overhead of separate function calls.

The actual plan shows the inlined UDF code as part of the main query operators, making it harder to identify the UDF’s specific contribution to the overall query performance.

Performance Implications

While inlining scalar UDFs can improve performance by reducing function call overhead, it can also lead to suboptimal execution plans. The query optimizer doesn’t have accurate statistics for UDFs, so it may make poor cardinality estimates and choose inefficient join algorithms or index usage.

Moreover, excessive use of scalar UDFs can result in complex, monolithic queries that are difficult to optimize and maintain.

Conclusion

Understanding why scalar UDFs appear in estimated plans but not in actual plans in SSMS is crucial for analyzing query performance. By recognizing the limitations of scalar UDFs and their impact on query optimization, you can make informed decisions about their usage and explore alternative approaches, such as inline table-valued functions (TVFs) or computed columns, to achieve better performance and maintainability.

To dive deeper into scalar UDF inlining and query optimization, check out the official Microsoft documentation.