Chris Hyde has started a series on executing external scripts with SQL Server ML Services:
We’ll start off with a simple step-by-step introduction to the sp_execute_external_script stored procedure. This is the glue that enables us to integrate SQL Server with the Python engine by sending the output of a T-SQL query over to Python and getting a result set back. . For example, we could develop a stored procedure to be used as a data set in an SSRS report that returns statistical data produced by a Python library such as SciPy. In this post we’ll introduce the procedure and how to pass a simple data set into and back out of Python, and we’ll get into manipulating that data in a future post.
If you’d like to follow along with me, you’ll need to make sure that you’re running SQL Server 2017 or later, and that Machine Learning Services has been installed with the Python option checked. Don’t worry if you installed both R and Python, as they play quite nicely together. The SQL Server Launchpad service should be running, and you should make sure that the ability to execute the sp_execute_external_script procedure is enabled by running the following code:
Chris’s talks on ML Services (either R or Python) were great and I expect this series to be as well.