Python UDFs 故障排除¶
本主题提供有关 Python UDFs（用户定义函数）的故障排除信息。
故障排除
问题：Anaconda 无法提供所需的 Python 库¶
Third-party Python libraries, which do not have C/C++ extensions, can be imported by UDFs directly via Snowflake stages. For more information, see Creating a Python UDF with code uploaded from a stage.
To learn how to submit a request to support additional Anaconda packages, see Using third-party packages.
问题：UDF 失败并显示错误“Function available memory exhausted”¶
减少 UDF 使用的内存量。
检查 UDF 代码是否存在错误或内存泄漏。
For more information, see Memory.
问题：我想提取 UDF 中的 ZIP 或其他档案¶
To see an example of how to upload a ZIP file to a Snowflake stage and then unzip it into the /tmp directory
inside the UDF, see Unzipping a staged file.
问题：UDF 性能缓慢¶
For information about how to improve the performance of UDFs, see Optimizing for scale and performance.
问题：ORGADMIN 角色未启用，因此无法使用 Anaconda 包¶
When going through the steps to get started using third-party packages from Anaconda, the organization administrator (ORGADMIN) role is required.
To resolve this problem, follow the instructions in Enabling the ORGADMIN role in an account.
问题：读取文件时 UDF 失败并显示错误“UnicodeDecodeError”¶
When you use the SnowflakeFile class to read files that contain non-text data, you must specify the input mode as binary.
Otherwise you might encounter the following error:
To resolve this problem, specify the input mode as binary by passing 'rb' for the mode argument (the second argument). For example:
技巧
Training machine learning (ML) models can sometimes be very resource intensive. Snowpark-optimized warehouses are a type of Snowflake virtual warehouse that can be used for workloads that require a large amount of memory and compute resources. For information on machine learning models and Snowpark Python, see Training Machine Learning Models with Snowpark Python.
If using a Python UDF in a masking policy, ensure the data type of the column, UDF, and masking policy match.
For troubleshooting information about third-party packages, see Known issues with third-party packages.