DSA-C03 Exam Dumps | You have deployed a custom model using Snowpark within Snowflake. The model is designed to predict customer

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Snowflake.DSA-C03.v2026-01-08.q143
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Question 121/143

You have deployed a custom model using Snowpark within Snowflake. The model is designed to predict customer churn, and you've wrapped it in a User-Defined Function (UDF) for easy use. The UDF takes several customer features as input and returns a churn probability. However, you notice the UDF's performance is slow, especially when scoring large batches of customers. Which of the following strategies would be most effective in optimizing the performance of your model deployment within Snowflake? Assume the UDF is already using vectorization techniques.

A. Increase the warehouse size used by Snowflake. This provides more resources for the UDF execution.

B. Re-write the UDF in SQL instead of Snowpark to avoid the overhead of the Snowpark API.

C. Utilize a vectorized UDF that can process multiple rows in a single call, further leveraging Snowflake's parallel processing capabilities. Ensure it supports the correct data types for both input and output. Consider using a Pandas UDF if Python is the underlying language.

D. Cache the results of the UDF using Snowflake's result caching feature. This will avoid re-executing the UDF for the same input values.

E. Implement row-level security on the input data. This enhances security and implicitly improves query performance because the model only processes authorized data.

Correct Answer: A,C

Options A and C are correct. Increasing the warehouse size provides more compute resources, leading to faster execution. Vectorized UDFs (especially Pandas UDFs for Python-based models) are highly efficient for batch processing, as they leverage Snowflake's parallel processing capabilities. B is incorrect as Snowpark UDFs are often more efficient due to their ability to use compiled languages and optimized libraries. Result caching (Option D) might help if the same input data is frequently used, but it won't improve the performance for new data. Row-level security (Option E) is primarily for security and won't directly improve UDF performance in this context.

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