SQL user defined functions
- qh2292 Qi Han
- wrote the problem
- wrote the solution and basic format to define a new function in SQL
- wrote the example and tutorial (together)
- js6594 Jiaying Shen
- wrote the Alternatives and Comparison
- wrote How UDFs Relate to Concepts from 4111
- wrote the example and tutorial (together)
In the database, there are often many places where built-in functions cannot meet the needs, complex logic needs to be implemented, or code repetitiveness needs to be simplified. Here are some examples:
- Formatting complex strings (e.g., cleaning phone numbers)
- Handling complex date logic (e.g., normalizing confusing date formats)
- Formulas in specific fields (e.g., compound interest calculation in the financial industry)
- Extract, transform and generate new features (e.g., generating classification labels based on user behavior)
SQL User Defined Functions (UDFs) allow users to create custom functions that accept columns of input, perform actions on the input, and return the result as a value. By encapsulating logic into reusable functions, UDFs improve maintainability and readability of SQL queries. They can be defined as either persistent or temporary, making them flexible for both recurring and ad hoc tasks.
Basic format to define a new function in SQL:
Scalar functions
-
Function_name: User-defined function name. The function name must conform to the identifier specification. The name must be unique in the database for its owner. -
@parameter_name: The parameter name of a user-defined function. One or more parameters can be declared in a create function statement. The @ symbol is used as the first character to specify the parameter name. -
data_type: The return type of the user-defined function. It can be a basic scalar type supported by SQL Server, except text, text, image, and time. - Between
beginandendis the function body, and it must include a return statement to return a value.
Inline table-valued functions
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Function_name: User-defined function name. The function name must conform to the identifier specification. The name must be unique in the database for its owner. -
RETURNS table: This sentence contains only the keyword table, indicating that this function returns a table. -
RETURN (select_stmt): The function body of an embedded table-valued function has only one return statement, and returns the embedded value through the select statement specified by the parameter select_stmt.
Another alternative to SQL user-defined functions (UDFs) is to use a programming language such as Python or R. This approach involves extracting data from the database, performing transformations and calculations in an external application, and then returning the results to the database. UDF is unique in that it can operate within the database, seamlessly embedded in queries, and maintain high performance and consistency. Although external queries allow to use more powerful computing tools, the increased latency due to data transmission and reliance on external code would become one of the unavoidable disadvantages.
In class, we learned how relational model use constraints like primary keys or check constraints to maintain data integrity. SQL User Defined Functions (UDFs) can provide additional functionality to the relational model and constraints by allowing custom rules or calculations. In traditional constraints (such as CHECK constraints), we can only define fixed rules, like "age must be between 18 and 60." However, in some cases, such static rules are insufficient, and dynamic calculations based on business logic are required.
Scalar UDFs are executed row-by-row, which means that for each row of data, the UDF is run once separately. This can result in slower queries, especially when processing large amounts of data, because they are not batch-optimized like normal SQL queries.
We know that SQL transactions ensure consistency and isolation. Since UDFs are read-only, they don’t modify the database, so they don’t interfere with transactions. This makes them safe to use in situations where maintaining transaction isolation is critical.
We would use our own project 1 as an example. FYI, https://colab.research.google.com/drive/1pXPxKprYpFgWSMcBl_yk0vWG2QoPItmY
Considering the user's specific health goals, we want to filter recipes based on the user's allergies.
In this function, we return a boolean value to determine whether a recipe is suitable for a certain user.
We can get the result of whether a recipe is suitable for a user more quickly by calling the function directly. When using this function, we can choose to have a certain user correspond to a certain recipe, or a certain user correspond to all recipes.
