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

2. Your Snowflake Native Application uses a combination of stored procedures and UDFs. You've implemented robust logging within your application to track usage and potential errors. You want to grant a Snowflake support engineer temporary access to these logs for troubleshooting purposes, minimizing the risk of exposing sensitive consumer dat a. Select the two statements below that describe best practices to ensure security and efficiency.

A) Create a new user role specifically for support and grant this role SELECT privileges on the logging tables without any filtering.
B) Create a dedicated view on the logging table that filters out sensitive data (e.g., PII) and grant the support engineer SELECT privileges on this view.
C) Grant the support engineer OWNERSHIP of the database containing the logging tables. This allows them full access for troubleshooting.
D) Implement row-level security (RLS) policies on the logging table to restrict access based on the support engineer's role.
E) Use a temporary table to copy the relevant log data, mask sensitive information using 'MASKING POLICY or 'ANONYMIZATION' and grant the support engineer SELECT access to the temporary table. Schedule the table to drop automatically after a short period (e.g. 24 hours).

3. You are packaging a Snowflake Native App that includes Python code and several supporting data files (e.g., configuration files, sample datasets). What are the correct steps to upload these files to a stage for inclusion in your application package, and how do you ensure the Python code is correctly referenced?

A) Use the 'snowcli' command-line tool to upload the files to a stage. In the setup.py file, ensure that the Python code is referenced correctly, and the data files are listed as package data.
B) Use 'snowcli' to create and manage stages. Structure the application directory appropriately, listing Python code and data files in 'manifest.yml' for correct packaging.
C) Upload the Python code directly to a Snowflake UDF using the web interface. Upload the data files to an external stage accessible via a URL, and reference them in the application code.
D) Employ the Snowflake JDBC driver to programmatically upload the files to an internal stage. Update the setup.py file to install the Python dependencies and reference the data files as resources.
E) Use the Snowflake web interface to upload all files to an internal stage. Reference the Python code within the setup.py file using relative paths.

4. You are tasked with publishing a Snowflake Native Application to the Snowflake Marketplace. Your application relies on specific external packages available through Anacond a. You've already built your application and are preparing to create the listing. Which steps are NECESSARY to ensure that consumer accounts can successfully install and use your application, considering external package dependencies?

A) Include a 'requirements.txt file within your application package listing all required Python packages and their versions.
B) Explicitly import all required external packages within the application's setup script using 'import
C) When creating the Snowflake Marketplace listing, specify the required external packages under the 'External Packages' section using the fully qualified package name (e.g., 'snowflake.ml.modeling').
D) Distribute the packages directly as part of the application code. This avoids external dependencies.
E) Consumers are automatically prompted to install any missing external packages upon installing the application; no specific action is required during listing creation.

5. A data science team is developing a Native App on Snowflake that requires access to data from multiple customer accounts (Reader Accounts). They need to ensure strict data governance and minimize the risk of data leakage. Which of the following approaches provides the MOST secure and scalable solution for accessing and managing this cross-account data?

A) Implement a data access service within the Native App that uses external functions to query data from consumer accounts, relying on network policies for security.
B) Package the data extraction logic directly into the Native App using User-Defined Functions (UDFs) that establish secure connections to each consumer account using separate credentials stored securely within the application package.
C) Utilize secure data sharing with data clean rooms, exposing the required datasets via views on each data clean room.
D) Create a shared database from each consumer account containing views over the required tables, granting SELECT privileges on these views to the application role.
E) Grant SELECT privileges directly to the application role on all relevant tables in the consumer accounts.

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