DSA-C03 Exam Dumps | You've created a Python UDF in Snowflake that uses the 'numpy' and libraries to perform complex statistical

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Question 35/143

You've created a Python UDF in Snowflake that uses the 'numpy' and libraries to perform complex statistical calculations on time-series data'. The UDF is deployed successfully, but when you execute it on a large dataset, you observe significant performance bottlenecks. Analyzing the execution plan reveals that the UDF is being executed serially for each row of the input data, preventing Snowflake from leveraging its parallel processing capabilities. What strategies can you employ to improve the performance and enable parallel execution of the UDF in Snowflake?

A. Increase the Snowflake warehouse size to provide more resources for serial execution.

B. Modify the UDF to accept a Pandas DataFrame as input instead of individual row values. Ensure your UDF is vectorized to process the entire DataFrame at once.

C. Rewrite the UDF using Snowflake's Java UDF functionality instead of Python, as Java is inherently faster for numerical computations.

D. Use the 'snowflake.snowpark' library to create a distributed Pandas DataFrame and perform computations directly within the Snowflake engine in a parallel manner.

E. Decompose the UDF into smaller, more manageable functions and register each as a separate UDF, hoping Snowflake will parallelize the execution of these smaller UDFs automatically.

Correct Answer: B,D

Options B and D are correct. Option B: Vectorizing the UDF by accepting a Pandas DataFrame allows the 'numpy' and 'scipy' operations to be applied efficiently on batches of data, leveraging the underlying parallelism of these libraries and Snowflake's engine. Option D: Using Snowpark's distributed Pandas DataFrame allows computations to be pushed down and executed in parallel within Snowflake. Option A only provides more resources but doesn't address the serial execution. Option C is not always guaranteed to be faster and introduces complexity of learning a new API. Option E doesn't guarantee that the UDFs will run in Parallel and also it increases the complexity of maintance.

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