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Welcome to a new post where we will explore the power and flexibility of User-Defined Functions (UDF) within Databricks SQL. These functions extend the built-in functions provided by SQL and can be customized to implement a wide array of tasks.
What are SQL UDFs?
In SQL parlance, a User-Defined Function (UDF) is a way for developers to extend the functionality of the SQL language. It allows the definition of operations not included in the standard SQL command set. So, in essence, you can create your function and call it in your SQL code.
SQL UDF Example
Let’s take a look at a simple example. We’ll create a function that multiplies a number by two:
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CREATE FUNCTION dbo.udf_multiplyByTwo(@n float) RETURNS float AS BEGIN RETURN @n * 2 END; |
Our function ‘udf_multiplyByTwo’ takes in one parameter of type float and returns a float. The function multiplies the input parameter by two and returns the result.
Testing the function
You can test the function like so:
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SELECT dbo.udf_multiplyByTwo(7) as Result; |
This query will return 14.0.
SQL UDFs in Databricks
In Databricks, we can use UDFs in a similar manner to extend Databricks’s SQL functionality.
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%sql CREATE FUNCTION example_function AS (x DOUBLE, y DOUBLE) RETURNS DOUBLE LANGUAGE sql AS $$ x*y; $$; |
This function named ‘example_function’ takes in two parameters, both of type double, and multiplies them together. This function can then be used in a SQL statement:
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%sql SELECT example_function(5.5, 5.0); |
The result of this query will be 27.5.
Final Thoughts
UDFs in Databricks SQL offer a compelling method to extend the power and functionality of SQL. With UDFs, your SQL can perform operations that are not within SQL’s original command set, offering you the flexibility and power to handle any data processing requirement you might encounter. Practice with the examples shared in this post and discover the true power of UDFs!