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Snowflake SnowPro Specialty - Native Apps Sample Questions:

1. You're developing a Snowflake Native Application and want to control access to different features based on roles. You have a Streamlit application that displays sensitive data, and you only want users with the 'DATA ANALYST and 'ADMIN' roles to be able to view this dat a. Which of the following methods or a combination of methods are MOST appropriate for enforcing this role-based access control within your Streamlit application and the underlying Snowflake resources?

A) Within the Streamlit application, use the function to check for a URL parameter containing the user's role. If the role matches or 'ADMIN', display the data; otherwise, display an error message. Grant 'SELECT' privilege on the underlying data tables to the DATA ANALYST and 'ADMIN' roles directly.
B) Create a custom python module that checks if the user's role matches "DATA_ANALYST or 'ADMIN' and configure it for role based access control.
C) Implement row-level security (RLS) policies on the underlying tables to filter data based on the user's role. Then, within the Streamlit application, simply display the data without any explicit role checks. The RLS policies will automatically ensure that users only see the data they are authorized to see. Grant 'SELECT privilege on the underlying data tables to the 'DATA ANALYST and 'ADMIN' roles directly.
D) Within the Streamlit application, use 'snowflake.connector' to execute 'SELECT and check if the returned role matches DATA ANALYST or 'ADMIN'. If so, display the data; otherwise, display an error message. Grant USAGE' privilege on a custom role, and grant 'SELECT on the underlying tables and USAGE on the schema to that custom role. Finally grant the 'DATA_ANALYST and 'ADMIN' roles to this custom role.
E) Create a stored procedure that checks the user's role using 'CURRENT and returns the requested data only if the role matches or ' ADMIN'. Call this stored procedure from your Streamlit application. Do not grant any direct privileges on the underlying tables to the 'DATA_ANALYST or 'ADMIN' roles. Set the 'EXECUTE AS CALLER property on the stored procedure.

2. You are tasked with developing a Snowflake Native Application that allows consumers to securely access and analyze data from an external API. Your application needs to handle API authentication using OAuth 2.0, refresh tokens automatically, and provide a user- friendly interface for consumers to configure the API connection. Which of the following steps are CRITICAL for ensuring secure and seamless integration with the external API within your Snowflake Native Application?

A) Utilize Snowflake's Secret objects to securely store the client ID and client secret. Use the object within your Snowflake Native App to make the application consumer-configurable.
B) Embed the OAuth 2.0 client library directly into your application's code and handle token management within the application logic.
C) Require consumers to manually configure the OAuth 2.0 connection details (client ID, client secret, token endpoint, etc.) within their Snowflake account and then pass these details as parameters to your application's functions.
D) Store the client ID and client secret directly within the application's setup script.
E) Use Snowflake's External Functions to call an API Gateway to obtain authentication tokens and then make calls to External API.

3. You are the provider of a Snowflake Native Application built with Scal
a. Consumers are reporting that a specific UDF, 'calculate_risk' , occasionally returns incorrect results for certain input datasets. You suspect an issue with the UDF's logic but struggle to reproduce the problem in your development environment. Given that you cannot directly access the consumer's data, what are the most effective strategies for diagnosing this issue?

A) Implement logging within the 'calculate_risk' UDF to capture input parameters and output values for a sample of executions. Store these logs in a secure table accessible only to the provider, subject to data governance policies. Utilize Snowflake's masking policies to mask the sensitive data and allow the provider to see only masked version, not the actual sensitive data.
B) Modify the UDF to include a 'debug' mode that performs additional checks and assertions. The consumer can enable this mode to collect diagnostic information and report any failures back to the provider. Consumer shares the error logs/code
C) Request the consumer to execute the UDF with the problematic datasets and provide the resulting incorrect output. Then, use Snowflake's query history and lineage features to trace the data flow and identify potential issues in the UDF's logic.
D) Request the consumer to provide anonymized sample data that triggers the issue. Use this data in your development environment to debug the UDF.
E) Implement comprehensive unit tests for the 'calculate_risk' UDF, covering a wide range of input values and edge cases. Ensure these tests pass before deploying new versions of the application.

4. You have created a Snowflake Native Application that includes a User-Defined Function (UDF) written in Python. The UDF processes JSON data and performs complex calculations. During testing in a consumer's account, you discover that the UDF is running slower than expected. What steps can you take to optimize the UDF's performance? (Select TWO)

A) Increase the warehouse size allocated to the consumer's account, as this directly impacts UDF execution speed.
B) Recompile the UDF with the latest version of the Snowflake runtime environment.
C) Leverage vectorization techniques within the Python UDF using libraries like NumPy to perform operations on entire arrays instead of individual elements.
D) Switch the UDF implementation from Python to SQL, as SQL UDFs are generally faster than Python UDFs.
E) Reduce the complexity of the UDF by simplifying the calculations and minimizing the amount of data processed.

5. A provider is developing a Snowflake Native App and utilizes event sharing to communicate state changes to consumers. After initial installation, a consumer reports not receiving any event notifications. The provider has verified the event table is populated correctly. Which of the following are the MOST likely reasons for this issue and how can the provider troubleshoot them?

A) The consumer has not explicitly granted the necessary privileges on the event table function to the role used by the app. Instruct the consumer to grant USAGE on the event table function to the app role.
B) Event sharing is inherently unreliable and Snowflake does not guarantee event delivery. The provider should implement alternative polling mechanisms.
C) The event table function is not correctly filtering events based on the consumer's application instance I Review the function logic to ensure proper filtering using APP_INSTANCE_ID().
D) The consumer has not refreshed their application instance metadata. Ask the consumer to execute SYSTEM$REFRESH_EXTERNAL_FUNCTIONS() in the application database.
E) The consumer's event table function does not have the correct security invoker privileges. Grant EXECUTE TASK on the event table function to the consumer role.

Solutions: