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Snowflake SnowPro Specialty - Native Apps Sample Questions:

1. You are developing a Streamlit application within a Snowflake Native Application that needs to access a secured view named 'sensitive_data' in the application's container. This view exposes aggregated and anonymized dat a. What minimum set of privileges must be granted to the 'app_public' application role to allow users to query this view from the Streamlit application?

A) GRANT USAGE ON SCHEMA application TO APPLICATION ROLE app_public; GRANT SELECT ON VIEW .application.sensitive_data TO APPLICATION ROLE app_public;
B) GRANT SELECT ON VIEW .application.sensitive_data TO APPLICATION ROLE app_public;
C) GRANT USAGE ON DATABASE TO APPLICATION ROLE app_public; GRANT SELECT ON VIEW .application.sensitive_data TO APPLICATION ROLE app_public;
D) GRANT USAGE ON SCHEMA application TO APPLICATION ROLE app_public; GRANT ALL PRIVILEGES ON VIEW application.sensitive_data TO APPLICATION ROLE app_public;
E) GRANT USAGE ON DATABASE .application TO APPLICATION ROLE app_public; GRANT SELECT ON VIEW .application.sensitive_data TO APPLICATION ROLE app_public;

2. You are developing a Snowflake Native Application that utilizes Snowpark Container Services (SPCS). Your application requires a Compute Pool configured with autoscaling capabilities to handle fluctuating workloads. However, you want to minimize costs when the application is idle. Which of the following considerations are MOST important when defining the 'MIN NODES' and 'MAX NODES' parameters for your Compute Pool, along with the 'AUTO RESUME setting?

A) The optimal configuration depends on the balance between cost and performance. A higher 'MIN_NODES' value provides faster initial response times but incurs higher costs when idle. 'AUTO RESUME should be set to TRUE if you want the pool to automatically restart based on incoming requests.
B) The 'AUTO_RESUME parameter is irrelevant as the compute pool automatically scales based on current workload. should be set to the expected average workload.
C) Compute Pool autoscaling is managed entirely by the underlying container orchestration system and Snowflake only provides basic resource allocation. The 'MIN NODES' and 'MAX NODES parameters are advisory only.
D) Setting to a non-zero value ensures that some resources are always available, leading to faster response times for initial requests. 'AUTO RESUME' should be set to FALSE to prevent unnecessary resource usage.
E) Setting to 0 allows the Compute Pool to scale down completely when idle, eliminating costs. 'AUTO_RESUME should be set to TRUE to automatically start the pool when a new request is received.

3. You're developing a Snowflake Native App with a Streamlit I-Jl. The app needs to read configuration data from a file named within your application package. The file contains sensitive information, and you want to ensure it's only accessible by your application's code and not directly readable by the consumer. What steps would you take to accomplish this?

A) Store 'config.json' in an internal stage and grant the 'READ' privilege on the stage to the consumer's role.
B) Store 'config.json' within the application package and read it using Python code within a stored procedure. Grant appropriate privileges on the stored procedure, but not on the 'config.json' file or the internal stage.
C) Store 'config.json' within the Streamlit code, and then encode and decode it to the original string when the user invokes the Streamlit application.
D) Store 'config.json' in a table within your application's schema and grant the 'SELECT' privilege on the table to the consumer's role.
E) Store 'configjson' outside the application package and read it directly from an external stage at runtime.

4. You are developing a Snowflake Native Application intended for the Snowflake Marketplace. Before listing your application, you want to ensure it adheres to Snowflake's best practices for security, performance, and usability. Which of the following steps should you take to validate your application prior to submission? (Choose three)

A) Manually review the application code to identify potential SQL injection vulnerabilities and optimize query performance.
B) Use Snowflake's built-in code scanning tools (if available in the future) to automatically identify security vulnerabilities and code quality issues.
C) Conduct thorough testing of the application on various Snowflake editions and sizes to ensure scalability and performance across different environments.
D) Deploy the application to a separate Snowflake account and simulate user interactions to validate the application's usability and functionality.
E) Submit your application code to a third-party security auditing firm for a comprehensive vulnerability assessment.

5. You are developing a Snowflake Native Application using Scala for a financial institution. The application processes sensitive transaction dat a. During consumer-side testing, the consumer reports intermittent 'java.lang.NullPointerException' errors. You suspect the issue lies within your UDE How can you effectively trace and debug this issue, considering data privacy requirements and without directly exposing sensitive consumer data in your logs?

A) Use Snowflake's event table to capture all exceptions, filtering for the UDF name. Redact potentially sensitive fields in the logs after extraction using a Python script executed on the provider side.
B) Utilize 'System.out.println' statements within the Scala UDF to print debug messages directly to the query result. The consumer can view these messages to identify the source of the error, with the provider having no visibility.
C) Rely solely on Snowflake's query history to identify failing queries. Analyze the input data and execution plan to infer the cause of the NullPointerException.
D) Implement a custom error handling mechanism in Scala that catches 'NullPointerException', logs a generic error message with a unique error code to the event table, and then re-throws a more descriptive exception to the consumer. The consumer can then report the error code to the provider for further investigation. The provider can analyze the code, without actual consumer sensitive data.
E) Implement structured logging within the Scala UDF using SLF4J and Logback. Include contextual information (e.g., transaction IDs, timestamps) at various stages of the UDF execution. Use Snowflake's masking policies on the event table to protect sensitive data during logging. This is the best method as it's the more granular and effective

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