SPS-C01 Exam Dumps | A data scientist has developed a Snowpark Python stored procedure named 'model

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Question 72/151

A data scientist has developed a Snowpark Python stored procedure named 'model_training'. This procedure utilizes a large machine learning model and requires significant compute resources. The data scientist wants to optimize the cost and performance of running this stored procedure. Which of the following strategies would be the MOST effective for achieving this goal?

A. Run the stored procedure on a larger Snowflake warehouse to reduce execution time, regardless of potential idle time.

B. Register the stored procedure with the '@sproc' decorator without specifying any warehouse size, letting Snowflake automatically manage the warehouse.

C. Specify a warehouse size using the 'warehouse' parameter within the '@sproc' decorator and leverage auto-suspend and auto-resume features to minimize costs when the procedure is idle.

D. Split the stored procedure into multiple smaller procedures and execute them sequentially on a smaller warehouse.

E. Convert the Python stored procedure to a SQL stored procedure to leverage Snowflake's SQL optimization engine.

Correct Answer: C

Specifying a warehouse size and using auto-suspend and auto-resume provides a balance between performance and cost. Option A might increase costs due to idle time. Option B relies on Snowflake's default warehouse, which might not be optimal. Option D could increase overall execution time due to overhead. Option E may not be feasible or efficient if the logic is heavily dependent on Python libraries. Therefore, specifically assigning an appropriate warehouse size with auto-suspend/resume is the most effective approach.

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