Snowflake Certified SnowPro Specialty - Snowpark - SPS-C01

You have JSON files stored in an internal stage named 'json_stage' within your Snowflake account. Each JSON file contains an array of product objects, with potentially nested structures. You need to create a Snowpark DataFrame to analyze this data, but the schema is complex and you want to avoid explicitly defining it in your Python code. Which of the following Snowpark code snippets will MOST effectively achieve this, assuming you have a Snowpark session object named 'session'?

• A.
  
• B.
  
• C.
  
• D.
  
• E.
  

Explanation: Only visible for PassExamDumps members. You can sign-up / login (it's free).

You have a Snowpark DataFrame 'employees df representing employee data'. You need to update the 'salary' column for employees in the 'Sales' department by applying a 10% increase. Which of the following Snowpark code snippets correctly performs this update? Assume a Snowflake table named 'employees' exists and 'employees df' is correctly created from it.

• A. Option E
• B. Option D
• C. Option C
• D. Option A
• E. Option B

Explanation: Only visible for PassExamDumps members. You can sign-up / login (it's free).

You are developing a Snowpark Python stored procedure that utilizes external Python libraries (e.g., 'requests', 'numpy'). What are the recommended steps for deploying this stored procedure to Snowflake, ensuring that all necessary dependencies are available during execution?

• A. Both A and B are correct methods to deploy the stored procedure.
• B. Include the installation commands (e.g., 'pip install requestS , 'pip install numpy') directly within the stored procedure's Python code. Snowflake will execute these commands during each invocation of the stored procedure.
• C. Package all required dependencies into a ZIP file and upload it to a Snowflake stage. Specify the stage path in the 'imports' parameter when creating the stored procedure.
• D. None of the above, Snowflake does not support external python libraries in stored procedures.
• E. List all required dependencies in the 'packages' parameter when creating the stored procedure. Snowflake automatically resolves and installs these dependencies from its managed Anaconda channel.

Explanation: Only visible for PassExamDumps members. You can sign-up / login (it's free).

Consider the following Snowpark Python code snippet intended to operationalize a stored procedure:

This code results in an error during registration. Which of the following actions would be MOST appropriate to fix the registration issue and ensure the stored procedure can be successfully operationalized?

• A. Add 'session.close()' at the end of the main function.
• B. Add in sproc.register.
• C. Remove the 'input_data' parameter from the 'main' function definition and access the input data directly using within the function.
• D. Define 'session' as a global variable before calling 'session.sproc.register' .
• E. Move the 'session.sproc.register' call outside of the 'main' function and execute it separately after the 'main' function definition.

Explanation: Only visible for PassExamDumps members. You can sign-up / login (it's free).

You have written a Snowpark Python function that utilizes a UDF to perform complex string manipulation on a DataFrame containing customer reviews. When deploying this function using '@sproc.test_utils.mock_snowflake environment, the test fails with a 'ModuleNotFoundError' indicating that a custom Python library (e.g., is not available. You have already confirmed that the library is installed in your local development environment. What is the MOST reliable way to ensure the UDF has access to this dependency during local testing?

• A. Use before defining the UDF to explicitly include the library as a zipped file. Ensure the zipped file contains the directory.
• B. Manually copy the directory into the 'ltmp' directory on your local machine before running the test. Snowpark will automatically detect libraries in this directory.
• C. Append the path to the library to the 'PYTHONPATH' environment variable before executing the local tests. This will make the library available to the Snowpark session during testing.
• D. Install the globally on your local machine using 'pip install
• E. Include the directory within the same directory as your Snowpark Python function and explicitly import it using a relative path (e.g., 'from .text_processing_lib import ...4).

Explanation: Only visible for PassExamDumps members. You can sign-up / login (it's free).