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Snowflake Certified SnowPro Specialty - Snowpark Sample Questions:

1. You have a Snowflake stage containing image files. You need to write a Snowpark Python application that extracts metadata (e.g., image resolution, format) from these images and stores the metadata in a Snowflake table. You want to leverage a Python library, such as Pillow (PIL), for image processing. Which of the following steps are necessary to correctly and efficiently implement this?

A) Create a Conda environment specification file ('environment.yml') that includes Pillow as a dependency. Upload the 'environment.ymr file to a Snowflake stage. Use 'session.add_packages' in the Snowpark session to load the Pillow library. Read the image files using , process them with Pillow, and then write the metadata to a Snowflake table using 'session.write_pandas()'.
B) Download all the image files to the Snowpark client, process them locally using Pillow, and then upload the extracted metadata to Snowflake using session
C) Upload the Pillow library as a zip file to a Snowflake internal stage. Create a Snowpark stored procedure. In the stored procedure code, import the Pillow library using 'import zipfile; sys.path.append('pillow.zip'); from PIL import Image'. Read the image files using , process them with Pillow to extract metadata, and then insert the metadata into the Snowflake table.
D) Use Snowpark's built-in image processing functions to extract metadata directly from the image files. This eliminates the need for external libraries like Pillow.
E) Create a Python UDF (User-Defined Function) that uses Pillow to extract metadata from the image files. Register the UDF with Snowflake. In a Snowpark DataFrame transformation, call the UDF for each image file to extract the metadata. Finally, write the resulting DataFrame to a Snowflake table.

2. Which of the following statements are correct regarding the authentication methods available when creating a Snowpark session?

A) OAuth with external Oauth providers (like Okta or Azure AD) is not supported in snowpark, and only username password can be used.
B) Using username/password authentication is the most secure and recommended approach for production environments.
C) Key pair authentication uses a private key to establish a secure connection without needing to store passwords directly in the code.
D) OAuth authentication requires pre-configuration in Snowflake and typically involves client IDs, client secrets, and refresh/access tokens.
E) Snowflake supports MFA(Multi-Factor Authentication) using Web Browser Authentication, which needs to be enabled at an account level.

3. When using key pair authentication with Snowpark, what security best practices should you implement to protect your private key?
(Select all that apply)

A) Grant broad access to the environment variable containing the private key to all developers.
B) Store the private key directly in the Snowpark code repository.
C) Store the private key in an environment variable or a secure secret management system (e.g., HashiCorp Vault, AWS Secrets Manager, Azure Key Vault).
D) Encrypt the private key at rest.
E) Regularly rotate the key pair.

4. You have a Snowpark DataFrame containing sales data with columns 'region' , and 'sales_amount'. You need to calculate the total sales amount for each region and then filter the results to only include regions where the total sales amount is greater than 10000. Which of the following Snowpark code snippets correctly implements this logic?

A)

B)

C)

D)

E)

5. You have a Snowpark Python UDF that performs sentiment analysis on customer reviews. The UDF relies on a pre-trained machine learning model stored as a file in a Snowflake stage. To enhance security, you want to create a secure UDF. Which of the following steps are necessary to achieve this?

A) Grant USAGE privilege on the stage containing the model file to the SNOWFLAKE.DATA_GOVERNANCE role.
B) Grant READ privilege on the stage containing the model file to the role that owns the secure UDF.
C) When creating the UDF, specify 'secure=True' in the 'CREATE FUNCTION' statement, and explicitly grant USAGE privilege on the stage containing the model file to the role that executes the UDF using 'GRANT USAGE ON STAGE TO ROLE
D) Ensure the function definition specifies a 'context' parameter to pass security context.
E) Wrap the UDF creation in a stored procedure with 'EXECUTE AS CALLER to elevate privileges and ensure model access.

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