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Databricks is a unified data analytics platform that combines data engineering and data science functionalities. In this blog post, we will discuss advanced SQL techniques, particularly focusing on writing SQL functions and stored procedures in Databricks. While SQL functions are used to perform operations, stored procedures contain multiple SQL statements to automate workflows.
Understanding SQL Functions
SQL functions are an integral part of query writing, offering a way to create reusable code for operations that are repeatedly needed. A function takes in parameters (if any), performs an action, and returns the result of the action as a value. The syntax to create a function is:
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CREATE FUNCTION function_name ([@parameter1 [type1], ...]) RETURNS return_data_type [WITH <common_table_expression_group>] AS BEGIN function_body RETURN scalar_expression END ; |
Creating a Simple SQL Function
Let’s create a function to calculate the square of a number:
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CREATE FUNCTION SquareNumber(@num float) RETURNS float AS BEGIN RETURN @num * @num END |
You can now call our SquareNumber function like this:
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SELECT dbo.SquareNumber(4.2) AS SquareResult; |
Writing Stored Procedures in Databricks
On the other hand, a stored procedure is a pre-compiled object which is compiled for the first time and its compiled format is saved which keeps the database the effort of compiling the same commands every time it is run. Stored procedures are useful in controlling access to data, preserving data integrity and improving productivity. The generalized syntax of a stored procedure in SQL is:
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CREATE PROCEDURE p<a href="mailto:rocedure_name @parameter1" >rocedure_name @parameter1</a> datatype [= default] [READONLY], ... AS SQL_statements GO; |
Stored Procedure Example
Consider an example stored procedure that returns the total quantity purchased for a specific product from Sales Data:
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CREATE PROCEDURE d<a href="mailto:bo.TotalQuantity @Product" >bo.TotalQuantity @Product</a> varchar(50) AS SELECT Product, SUM(Quantity) AS TotalQuantity FROM SalesData WHERE Product = @Product GROUP BY Product; GO |
To call the stored procedure, we would use:
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EXEC dbo.TotalQuantity 'Apple'; |
Conclusion
Learning to write SQL functions and stored procedures and using them strategically within Databricks can greatly increase the proficiency and efficiency of your data handling tasks. As with learning any coding method, frequent practice, constant learning and embracing a problem-solving mindset are key to becoming proficient at SQL programming within Databricks.