SPS-C01 Exam Dumps | You are building a Snowpark application that uses a Python UDF to perform sentiment analysis on customer

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Snowflake.SPS-C01.v2026-08-07.q151
Question 34

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Question 34/151

You are building a Snowpark application that uses a Python UDF to perform sentiment analysis on customer reviews. The UDF relies on a large pre-trained machine learning model loaded from a file. During execution, you encounter 'Out of Memory' errors within the UDF. Considering the constraints of the Snowpark execution environment and the need to optimize resource usage, which of the following steps is the MOST effective in addressing this issue and ensuring the application's stability and performance?

A. Increase the overall size of the Snowflake warehouse to provide more memory for UDF execution. The Snowflake environment will automatically allocate more memory to UDFs when available.

B. Implement lazy loading of the machine learning model within the UDF, ensuring that the model is loaded only when it's first needed, and then cached for subsequent calls within the same UDF invocation.

C. Break down the customer reviews into smaller chunks and process them in batches within the UDF, clearing the model from memory after each batch to reduce overall memory consumption.

D. Use Snowpark's 'sproc' to register the UDF as a stored procedure instead ofa UDF, as stored procedures typically have more memory allocated to them.

E. Optimize the model itself by reducing it's size through quantization or distillation, and re-upload the smaller model to the Snowflake stage for the UDF to use.

Correct Answer: B,E

Lazy loading can reduce initial memory footprint of the UDF. Further, the first time when model is requested, it will be loaded in the UDF and cached for subsequent calls. This avoids reloading the same model again and again. Optimizing the model can reduce the memory footprint of the model to the point it no longer causes out of memory issues. Increasing warehouse size may help but won't address the underlying issue. Breaking down the reviews doesn't solve the memory issue within each batch. Stored procedures do not necessarily have more memory allocated than UDFs.

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