Defining Result Sets With ML Services

Kevin Feasel


Python, R

Dave Mason covers a pain point in SQL Server Machine Learning Services:

The example above is so simple, defining the RESULT SETS poses no problems. But what if the format of the output isn’t known at design time? R (or Python) might take the input data set and add, remove, or change columns conditionally. Further, the input data set might not even be known at design time. How would you define the RESULT SETS at run time?

WITH RESULT SETS needs a MAKE_A_GUESS or FIGURE_IT_OUT option. If there’s some other type of “easy button” for this, I haven’t found it.

It would be nice if the service could the ability to read the data frame columns and use those by default.

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