This section explains different ways to execute a Python function without pulling the data outside of Database Engine 20. Consider a scenario where you want to run analytics capabilities on the data residing in Database Engine 20, that are not already present in teradataml built-in functionality.
teradataml provides functions where you can apply your own logic to process and transform data within teradataml DataFrame. Use these functions/DataFrame methods to address specific data processing requirements beyond the built-in functions provided by teradataml.
- These functions avoid pulling data out of Database Engine 20. Instead, the Python function is pushed to Database Engine 20, eliminating data movement between the client and Database Engine 20.
- teradataml UDF is a Python user defined function, and it is different from the Teradata UDF which offers support for C++/C/Java UDF functions.
- udf - Function decorator
- UDF functions
- DataFrame methods
Use of teradataml UDF versus DataFrame Methods provides a breakdown differences between teradataml UDF versus DataFrame methods, and when to use each.