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Snowflake SnowPro Specialty - Native Apps Sample Questions:

1. A Snowflake Native App provider is using a Snowpark Python UDF to process data before writing it to an event table for consumption by consumer applications. The UDF fails intermittently with a 'Java heap space' error. Which of the following strategies are MOST effective in mitigating this error?

A) Implement batch processing within the UDF to process data in smaller chunks, reducing the memory footprint at any given time.
B) Optimize the Python UDF code to use more memory-efficient data structures and algorithms, reducing overall memory consumption.
C) Increase the warehouse size used by the consumer application instance, as this controls the memory available to the UDF during event processing.
D) Configure the event table function to use a larger warehouse size using the EXECUTE AS OWNER clause.
E) Switch to a Java UDF instead of a Python UDF, as Java UDFs inherently have better memory management in Snowflake.

2. Consider the following Snowflake Native App setup script snippet. The intention is to create an application role and grant it the necessary privileges to execute a stored procedure named 'MY PROCEDURE' within the application's data container. However, the script is not working as expected, and the stored procedure is failing with permission errors. Identify ALL of the issues in the following code.

A) The application role 'app_public' cannot be created inside the setup script.
B) The application role must be granted the 'USAGE privilege on the database that contains the schema.
C) The 'EXECUTE' privilege on the stored procedure should be granted to the 'application' role, not 'app_public' .
D) The setup script does not require any additional privileges to assign 'EXECUTE on PROCEDURE
E) The 'USAGE privilege on the schema containing the stored procedure is missing.

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

4. A data science team is developing a Snowflake Native Application that provides predictive analytics for financial institutions. The application requires access to usage data from consumer accounts, but only aggregated and anonymized data should be exposed. As the application provider, you need to grant the necessary privileges while adhering to the principle of least privilege. Which combination of global privileges and application logic will achieve this?

A) Grant the READ global privilege on the account metadata and use Snowflake's masking policies within the application to anonymize sensitive data.
B) Grant the ACCOUNTADMIN role to the application and rely on the application code to filter and anonymize the data.
C) Create a custom role with the MONITOR USAGE global privilege, grant this role to the application, and use secure views within the application to expose only the aggregated and anonymized data.
D) Grant the IMPORTED PRIVILEGES global privilege on the account and rely on data sharing agreements to control access to the aggregated and anonymized data.
E) Grant the USAGE global privilege on the account and implement stored procedures within the application that perform the aggregation and anonymizatiom

5. You are developing a Snowflake Native Application that needs to be deployed across multiple Snowflake accounts. The application includes a setup script that creates several tables and stored procedures. However, some consumers might have naming conflicts with the objects created by your setup script. Which of the following strategies can you use to minimize naming conflicts and ensure smooth application deployment? (Select all that apply)

A) Prefix all objects created by the setup script with a unique, application-specific identifier.
B) Package all application objects into a dedicated schema within the consumer's database.
C) Dynamically generate object names within the setup script using the application's name and a random suffix.
D) Utilize the 'CREATE OR REPLACE syntax for all objects in the setup script to overwrite any existing objects.
E) Instruct consumers to drop any conflicting objects before installing the application.

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