xloya opened a new issue, #6158: URL: https://github.com/apache/gravitino/issues/6158
### Describe the feature In enterprise production practice, if the built-in functions of the computing engine cannot meet user needs, users usually customize UDFs(User-Defined-Functions) through relevant interfaces and reference them in the engine. Especially for scenarios that require a lot of reuse, it is very important to effectively manage these custom functions. In Xiaomi's internal practice, there is also a UDF management system that basically meets user needs (limited to Spark/Flink, and there is no good support for AI + Python scenarios). As a unified Data / AI metadata center, I think Gravitino can also support UDFs management in Data / AI scenarios. The following are some commercial product practices: 1. Aliyun: https://help.aliyun.com/zh/flink/user-guide/manage-udfs 2. UnityCatalog: https://docs.databricks.com/en/udf/unity-catalog.html ### Motivation _No response_ ### Describe the solution _No response_ ### Additional context _No response_ -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
