Executing Python Functions Inside Analytics Database | Teradata Package for Python - Executing Python Functions Inside Analytics Database - Teradata Package for Python

Teradata® Package for Python User Guide

Deployment
VantageCloud
VantageCore
Edition
Enterprise
IntelliFlex
VMware
Product
Teradata Package for Python
Release Number
20.00
Published
December 2024
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en-US
ft:lastEdition
2025-01-23
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rkb1531260709148
Product Category
Teradata Vantage

This section explains different ways to execute a Python function without pulling the data outside of Analytics Database. Consider a scenario where you want to run analytics capabilities on the data residing in Analytics Database, 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 Analytics Database. Instead, the Python function is pushed to Analytics Database, eliminating data movement between the client and Analytics Database.
  • 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.

Use of teradataml UDF versus DataFrame Methods provides a breakdown differences between teradataml UDF versus DataFrame methods, and when to use each.