User-Defined Functions - SQL Server to Aurora PostgreSQL Migration Playbook
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User-Defined Functions

Feature compatibility Amazon SCT / Amazon DMS automation level Amazon SCT action code index Key differences


                              Three star feature compatibility


                              Three star automation level

N/A

Syntax and option differences.

SQL Server Usage

User-Defined Functions (UDF) are code objects that accept input parameters and return either a scalar value or a set consisting of rows and columns. You can use T-SQL or Common Language Runtime (CLR) code to implement SQL Server UDFs.

Note

This section doesn’t cover CLR code objects.

Function invocations can’t have any lasting impact on the database. They must be contained and can only modify objects and data local to their scope (for example, data in local variables). Functions aren’t allowed to modify data or the structure of a database.

Functions may be deterministic or non-deterministic. Deterministic functions always return the same result when you run them with the same data. Non-deterministic functions may return different results each time they run. For example, a function that returns the current date or time.

SQL Server supports three types of T-SQL UDFs: Scalar Functions, Table-Valued Functions, and Multi-Statement Table-Valued Functions.

SQL Server 2019 adds scalar user-defined functions (UDF) inlining. Inlining transforms functions into relational expressions and embeds them in the calling SQL query. This transformation improves the performance of workloads that take advantage of scalar UDFs. Scalar UDF inlining facilitates cost-based optimization of operations inside UDFs. The results are efficient, set-oriented, and parallel instead of inefficient, iterative, serial run plans. For more information, see Scalar UDF Inlining in the SQL Server documentation.

Scalar User-Defined Functions

Scalar UDFs accept zero or more parameters and return a scalar value. You can use scalar UDFs in T-SQL expressions.

Syntax

CREATE FUNCTION <Function Name> ([{<Parameter Name> [AS] <Data Type> [= <Default
Value>] [READONLY]} [,...n]])
RETURNS <Return Data Type>
[AS]
BEGIN
<Function Body Code>
RETURN <Scalar Expression>
END[;]

Examples

The following example creates a scalar function to change the first character of a string to upper case.

CREATE FUNCTION dbo.UpperCaseFirstChar (@String VARCHAR(20))
RETURNS VARCHAR(20)
AS
BEGIN
RETURN UPPER(LEFT(@String, 1)) + LOWER(SUBSTRING(@String, 2, 19))
END;
SELECT dbo.UpperCaseFirstChar ('mIxEdCasE');

Mixedcase

User-Defined Table-Valued Functions

Inline table-valued UDFs are similar to views or a Common Table Expressions (CTE) with the added benefit of parameters. You can use inline table-valued UDFs in FROM clauses as subqueries. Also, you can join inline table-valued UDFs to other source table rows using the APPLY and OUTER APPLY operators. In-line table-valued UDFs have many associated internal optimizer optimizations due to their simple, view-like characteristics.

Syntax

CREATE FUNCTION <Function Name> ([{<Parameter Name> [AS] <Data Type> [= <Default
Value>] [READONLY]} [,...n]])
RETURNS TABLE
[AS]
RETURN (<SELECT Query>)[;]

Examples

The following example creates a table-valued function to aggregate employee orders.

CREATE TABLE Orders
(
  OrderID INT NOT NULL PRIMARY KEY,
  EmployeeID INT NOT NULL,
  OrderDate DATETIME NOT NULL
);
INSERT INTO Orders (OrderID, EmployeeID, OrderDate)
VALUES
(1, 1, '20180101 13:00:05'),
(2, 1, '20180201 11:33:12'),
(3, 2, '20180112 10:22:35');
CREATE FUNCTION dbo.EmployeeMonthlyOrders
(@EmployeeID INT)
RETURNS TABLE AS
RETURN
(
  SELECT EmployeeID,
    YEAR(OrderDate) AS OrderYear,
    MONTH(OrderDate) AS OrderMonth,
    COUNT(*) AS NumOrders
  FROM Orders AS O
  WHERE EmployeeID = @EmployeeID
  GROUP BY EmployeeID,
    YEAR(OrderDate),
    MONTH(OrderDate)
);
SELECT *
FROM dbo.EmployeeMonthlyOrders (1)

EmployeeID  OrderYear  OrderMonth  NumOrders
1           2018       1           1
1           2018       2           1

Multi-Statement User-Defined Table-Valued Functions

Multi-statement table-valued UDFs, such as In-line UDFs, are also similar to views or CTEs with the added benefit of parameters. You can use multi-statement table-valued UDFs in FROM clauses as sub queries. Also, you can join multi-statement table-valued UDFs to other source table rows using the APPLY and OUTER APPLY operators.

The difference between multi-statement UDFs and the inline UDFs is that multi-statement UDFs aren’t restricted to a single SELECT statement. They can consist of multiple statements including logic implemented with flow control, complex data processing, security checks, and so on.

The downside of using multi-statement UDFs is that there are far less optimizations possible and performance may suffer.

Syntax

CREATE FUNCTION <Function Name> ([{<Parameter Name> [AS] <Data Type> [= <Default
Value>] [READONLY]} [,...n]])
RETURNS <@Return Variable> TABLE <Table Definition>
[AS]
BEGIN
<Function Body Code>
RETURN
END[;]

For more information, see CREATE FUNCTION (Transact-SQL) in the SQL Server documentation.

PostgreSQL Usage

For more information, see Stored Procedures.

Syntax

CREATE [ OR REPLACE ] FUNCTION
name ( [ [ argmode ] [ argname ] argtype [ { DEFAULT | = } default_expr ] [, ...]] )
[ RETURNS rettype
| RETURNS TABLE ( column_name column_type [, ...] ) ]
{ LANGUAGE lang_name
| TRANSFORM { FOR TYPE type_name } [, ... ]
| WINDOW
| IMMUTABLE | STABLE | VOLATILE | [ NOT ] LEAKPROOF
| CALLED ON NULL INPUT | RETURNS NULL ON NULL INPUT | STRICT
| [ EXTERNAL ] SECURITY INVOKER | [ EXTERNAL ] SECURITY DEFINER
| PARALLEL { UNSAFE | RESTRICTED | SAFE }
| COST execution_cost
| ROWS result_rows
| SET configuration_parameter { TO value | = value | FROM CURRENT }
| AS 'definition'
| AS 'obj_file', 'link_symbol'
} ...
[ WITH ( attribute [, ...] ) ]