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Snowflake SnowPro Specialty - Native Apps Sample Questions:

1. Consider the following Java UDF code snippet intended for use in a Snowflake Native Application. The UDF is designed to retrieve data from an external REST API. The code throws a 'java.net.SocketTimeoutException' intermittently when the API takes longer than expected to respond. How can you best handle this exception within the UDF to provide a more informative error message to the consumer and prevent the entire application from failing?

A)

B)

C)

D)

E)

2. A Snowflake Native App provider is troubleshooting an issue where consumer installations intermittently fail. The provider suspects that certain installation parameters are causing conflicts. The provider has implemented an event table to track installation attempts and errors. Which of the following SQL statements is the MOST effective way to identify the installation parameters that are most frequently associated with failed installations? Assume the event table is named "INSTALLATION EVENTS and contains columns 'INSTALLATION ID, 'STATUS' (success/failure), and PARAMETERS' (a VARIANT column storing a JSON object of installation parameters).

A)

B)

C)

D)

E)

3. An ISV is developing a data analytics application using Snowflake Native Apps. The application allows consumers to define custom data refresh schedules. These schedules are managed by stored procedures within the application. The stored procedures need to update a shared table (using SQL MERGE command) located in a different database (managed by the ISV) within the consumer's account. The Application provider doesn't want to give access to the underlying tables to the consumer. To achieve this, which of the following GRANT statements are needed to configure the correct set of privileges for the ISV's Application Role(s) to perform MERGE operations from inside the consumer's environment? (Select all that apply.)

A) GRANT INSERT, UPDATE, DELETE ON TABLE .. TO ROLE ;
B) GRANT ALL PRIVILEGES ON WAREHOUSE TO ROLE ;
C) GRANT USAGE ON SCHEMA TO ROLE ;
D) GRANT SELECT ON ALL TABLES IN DATABASE TO ROLE ;
E) GRANT USAGE ON DATABASE TO ROLE ;

4. Consider the following scenario: You're developing a Snowflake Native Application that requires both data loading and complex analytical queries. You plan to use separate warehouses to optimize performance and manage resources effectively. Given the requirements, which of the following warehouse configurations is the MOST appropriate?

A) Two warehouses: one dedicated to data loading, configured with to save costs and other warehouse for analytical queries.
B) One warehouse sized 'X-SMALL' for data loading and another sized URGE' for analytical queries.
C) Two warehouses: one with 'AUTO SUSPEND = 60' for data loading and another with 'AUTO SUSPEND = 3600' for analytical queries.
D) One large warehouse to handle both data loading and analytical queries, sharing resources to minimize costs.
E) Two warehouses: one dedicated to data loading configured with "WAREHOUSE_SIZE = X-SMALL' and another for analytical queries configured with 'WAREHOUSE SIZE = LARGE and 'MAX CONCURRENCY LEVEL = 8'.

5. 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 '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.
B) 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.
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) 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.
E) 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.

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