DSA-C03 Exam Dumps | You are tasked with training a machine learning model within Snowflake using a Python UDTF. The UDTF

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Question 26/143

You are tasked with training a machine learning model within Snowflake using a Python UDTF. The UDTF is intended to process incoming sales data, calculate features, and update the model incrementally. The model is a simple linear regression using scikit-learn. Your initial attempt fails with a 'ModuleNotFoundError: No module named 'sklearn" error within the UDTF. You have already confirmed that scikit-learn is available in your Anaconda channel and specified it during session creation. Which of the following actions would MOST directly address this issue and allow the UDTF to successfully import and use scikit-learn?

A. Recreate the Anaconda environment and ensure that the 'sklearn' package is installed specifically within the environment's 'site-packages' directory. Then, recreate the Snowflake session.

B. Include ' import snowflake.snowpark; session = snowflake.snowpark.session.get_active_session()' within the UDTF code to explicitly initialize the Snowpark session before importing sklearn. Ensure that scikit-learn is included in the 'imports' argument of the 'create_dataframe' method.

C. Ensure that the Anaconda channel containing 'sklearn' is explicitly activated at the account level using the 'ALTER ACCOUNT command. Verify the channel is listed in 'SHOW CHANNELS'.

D. When creating the UDTF, use the 'PACKAGES' parameter to explicitly specify the 'skiearn' package. For example: 'CREATE OR REPLACE FUNCTION RETURNS TABLE LANGUAGE PYTHON RUNTIME_VERSION = '3.8' PACKAGES = ('snowflake-snowpark-python','scikit-learn') ...

E. Explicitly copy the 'sklearn' directory and its dependencies directly into the same directory as your UDTF definition script on the Snowflake stage, then reference them using relative paths within the UDTF.

Question 26/143

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