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Warehousing & Analytics
Engage in discussions on data warehousing, analytics, and BI solutions within the Databricks Community. Share insights, tips, and best practices for leveraging data for informed decision-making.
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Python UDTF

data-grassroots
New Contributor III

Attempting to create a Python UDF and receiving an error stating it's not supported in my environment.

running on SQL Serverless Cluster - Preview (v 2025.16)

[FEATURE UNAVAILABLE]

Python UDTF is not supported in your environment.

To use this feature, please contact Databricks Support. SQLSTATE: 56038

 

create function _rrr_taxonomy_test()
RETURNS TABLE(dept string, cat string, subcat string)
LANGUAGE PYTHON
AS
$$
s = '''select
custom_department as dept,
custom_category as cat,
coalesce(custom_sub_category, '') as subcat
from item'''
 
return spark.sql(s)
$$
1 REPLY 1

nayan_wylde
Honored Contributor

Currently Serverless supports only scaler valued function not table valued function. also you need to provide the catalog and schema in the function.

You can create using a pro compute

create function {catalog_name}.{schema_name}._rrr_taxonomy_test()
RETURNS TABLE(dept string, cat string, subcat string)
LANGUAGE PYTHON
AS
$$
= '''select
custom_department as dept,
custom_category as cat,
coalesce(custom_sub_category, '') as subcat
from item'''
 
return spark.sql(s)
$$
 
 
I tried this function in serverless and it worked it is a scaler valued function.
 
create function {catalog_name}.{schema_name}._rrr_taxonomy_test_1()
RETURNS string
LANGUAGE PYTHON
AS
$$
= '"Hello World"
 
 
return s
$$