Saturday, 2 November 2024

Compute scalar operator in SQL Server execution plan

The Compute Scalar Operator in SQL Server execution plans is used to compute new values for each row based on existing data or expressions in the query. These computations can include things like evaluate expression, arithmetic operations, type conversion, string manipulations, function calls, or column value transformations.

Icon of Compute scalar

See the example

Arithmetic Expression: See below query

select ProductID,Name,StandardCost,ListPrice from Production.Product

See the execution plan

This execution plan is simple. Let’s add Arithmetic Expression in the query. Here we are calculating the total price as standardcost*ListPrice. See below

Compute scalar is generated. See the property.

See the example for type conversion

Here we are converting the ListPrice column value to varchar from decimal.

select ProductID,Name,StandardCost,cast(ListPrice as varchar(100)) as ListPrice

 from Production.Product

Se the property of compute scalar.

Build in function or User Defined function (UDF):

In this example we are using the Build in function LEN to find the length of the name.

select ProductID,Name,LEN(Name) as Size_of_Name

 from Production.Product

 

Compute scalar is generated. See the property of this operator.


The Compute Scalar Operator is usually lightweight and does not significantly impact query performance in most cases. However, there are some situations where the Compute Scalar operator can become a bottleneck, especially if we are using build in function or UDF or Type conversion. See In the above example we cost of completed scalar is 0 but here cost 1.

For the performance point of view avoid Expensive Scalar UDFs and If possible, replace scalar user-defined functions with inline table-valued functions (TVFs), which are generally more efficient because they avoid row-by-row processing. Also we can Minimize Type Conversions and avoid implicit conversions whenever possible by explicitly specifying the correct data types in our schema and queries. Pre compute Values in Views or Computed Columns if possible.

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