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Snowflake SnowPro Specialty - Native Apps Sample Questions (Q40-Q45):

NEW QUESTION # 40
You have a Snowflake Native Application that utilizes a managed table. After upgrading your application to version 2.0, some users report that they are missing data in the managed table. After investigation, you realize version 2.0 changed the schema of the managed table and also did not properly migrate all the data from old format into new format. Which of the following steps should be taken to address the missing data after upgrading a Snowflake Native Application?

A. Since managed tables are fully managed by Snowflake, contact Snowflake support to initiate a data recovery process in each affected consumer account.
B. Create a new version 2.1 that includes a data migration script to transfer data from the old schema (as it existed in version 1.0) to the new schema in version 2.0. Use release directives to upgrade affected users to version 2.1 after staging.
C. Create a new version 2.1. Within version 2.1's setup script, dynamically detect if the application is an upgrade from 1.0 and, if so, execute the data migration script to transfer data from the old schema to the new schema.
D. Manually insert the missing data into the managed table in each consumer's account, contacting affected users to coordinate the data entry.
E. Rollback all users to version 1.0 and then perform the schema migration directly on the consumer's account using custom SQL scripts.

Answer: C

Explanation:
Option D is the correct approach. By dynamically detecting the upgrade and running a data migration script, the application ensures data integrity during the upgrade process. The data migration script will convert data from old format to new format. Option A is almost correct, however we don't assume the user is at 1.0. The application may be updated from earlier versions as well. Option B is not feasible due to operational overhead of doing it for each consumers and requires high privilege on consumer side which is not allowed for native apps. Option C is not practical or scalable. Managed tables are managed by your application code within the package, so Snowflake support won't perform data manipulation (Option E).

NEW QUESTION # 41
Consider the following 'manifest.yml' file for a Snowflake Native App:

A. The application version will be automatically assigned by Snowflake during the installation process on the consumer side.
B. The application will fail to install because the version property is missing. Each version must explicitly be specified in the manifest file.
C. The application version will default to '0.0.1'. If the application includes a view, then the view needs access to the user data and must have a privilege declared to allow users to view data from the application.
D. The application version will default to '0.1.0' and the application can be installed successfully by any consumer account.
E. The application will fail to install because no 'privileges' are listed in the manifest file. All applications must declare the necessary privileges.

Answer: B

Explanation:
A valid version is mandatory in 'manifest.yml' to install native apps. When version is missing, the installation will fail.

NEW QUESTION # 42
You've installed a Snowflake Native Application that provides advanced data analytics. The application requires a consumer-defined function (UDF), 'MASK SENSITIVE DATA, to be created in their account and used by the application. The application's setup script includes logic to check for the UDF's existence, but you want to ensure the application gracefully handles the case where the consumer has not yet created the UDF. Which of the following strategies can you implement to improve the application's resilience and provide a better user experience in this scenario? Select all that apply.

A. Require the consumer to create the UDF before installing the application. The application setup script should fail if the UDF is not found, preventing installation.
B. Dynamically generate the application code using a stored procedure, only including the parts of the code that rely on if the function exists. Use 'SYSTEM$GET PRIVILEGES()' to check existence.
C. Within the application's SQL code, use the 'TRY FUNCTION' function to call 'MASK SENSITIVE DATA'. If the UDF does not exist, 'TRY FUNCTION' will return 'NULL' instead of raising an error.
D. In the application's setup script, create a placeholder UDF with the same name and signature as 'MASK SENSITIVE DATA' that returns 'NULL'. The application logic can then handle 'NULL' values appropriately until the consumer provides the actual UDF.
E. Implement error handling within the application's code to catch the 'SQL compilation error: UDF does not exists exception. Provide a user-friendly error message and instructions on how to create the UDF.

Answer: C,E

Explanation:
Options B and C are the best strategies for handling the missing UDF gracefully. 'TRY_FUNCTION' allows the application to continue running even if the UDF is not present, while error handling provides a clear and informative message to the user. Option A is problematic because it introduces a UDF that is not the intended function, potentially leading to data inconsistencies. Option D creates a rigid dependency and a poor user experience. Option E adds unnecessary complexity.

NEW QUESTION # 43
Which of the following statements regarding warehouse sizing and configuration for a Snowflake Native Application are true?

A. The 'AUTO SUSPEND' parameter controls how long a warehouse remains active after executing queries, impacting cost.
B. A larger warehouse size always guarantees faster query execution, regardless of the query's characteristics.
C. Warehouse size cannot be changed after it is created.
D. The 'MAX CONCURRENCY LEVEL' parameter helps manage the number of queries that can be executed concurrently on the warehouse.
E. The parameter determines if the warehouse is used for data loading vs query processing.

Answer: A,D

Explanation:
Warehouse size can be changed after creation using 'ALTER WAREHOUSE statement. A larger warehouse is not always faster; it depends on the query's design and data volume. The 'AUTO SUSPEND' parameter is crucial for cost control as it determines the idle time before automatic suspension. While Snowflake has virtual warehouses, the ' WAREHOUSE_TYPE parameter doesn't exist. 'MAX CONCURRENCY LEVEL' is essential for managing concurrent queries and preventing resource contention, improving overall application performance.

NEW QUESTION # 44
You are developing a Snowflake Native Application that uses Streamlit to provide a user interface for data analysts. The application accesses sensitive customer data residing in a managed database. To enhance security, you want to implement row-level security (RLS) based on the user's role. You have the following Streamlit code snippet:

Which of the following actions should you take to implement RLS in the Snowflake Native App, ensuring only authorized users can view specific rows of 'customer_data'? Assume the already contains necessary credentials. Choose the most secure and efficient method.

A. Implement RLS directly within the Streamlit application by filtering the 'data' DataFrame based on the user's role before displaying it using 'st.dataframe'. Store user roles in a separate table and fetch them using a different database connection.
B. Use Snowflake's masking policies combined with a secure view. The masking policy reveals data based on the user's role. Grant the Streamlit application's role access to the secure view.
C. Create a secure view in Snowflake that implements RLS based on the role of the user executing the query. Grant the Streamlit user access to this view instead of the base table, and modify the 'get_data' function to query the view.
D. Implement a custom Python decorator that checks user roles before executing the 'get_data' function. Raise an exception if the user lacks the necessary role.
E. Modify the SQL query within the 'get_data' function to include a 'WHERE clause that filters data based on the current Streamlit user's username obtained using 'st.session_state.user.username' .

Answer: B

Explanation:
Using Snowflake's masking policies and secure views is the most secure and efficient method. It centralizes RLS within Snowflake, leveraging its security features. Option A is vulnerable to SQL injection if 'st.session_state.user.username' is not properly sanitized. Option B is better, but masking policies provide more granular control and data obfuscation. Option C pushes security logic to the application layer, which is less secure. Option E adds unnecessary complexity and overhead.

NEW QUESTION # 45
......

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Snowflake SnowPro Specialty - Native Apps Sample Questions (Q40-Q45):

Free PDF 2026 Snowflake High Pass-Rate NAS-C01: SnowPro Specialty - Native Apps Complete Exam Dumps

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