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Snowflake SnowPro Specialty - Native Apps Sample Questions:

1. Your Snowflake Native Application needs to integrate with an external Python library (e.g., 'requests' ) to fetch data from a third-party API. You have packaged the library using Anacond a. How do you correctly reference and use this external library within a Python UDF in your application?

A) Use 'snowflake.ingest.SimplelngestManager' to manage the library dependencies within the application's metadata.
B) Create a stage to store the Anaconda packages and reference them when calling the UDF from Streamlit.
C) Specify the library in the 'imports' clause when creating the UDF using the opackageS decorator. For example:

D) Install the 'requests' library on each Snowflake virtual warehouse used by the application.
E) Import the library directly in the UDF code using 'import requests'. Snowflake automatically handles external dependencies.

2. You are developing a Snowflake Native Application that performs complex data transformations. You need to monitor the application's performance, identify bottlenecks, and track resource consumption. Which of the following approaches would effectively establish observability and telemetry for your application, ensuring you can gather granular insights into its operations?

A) Leverage Snowflake's event tables and Streamlit to visualize the performance and consumption of resources used by the application.
B) Implement custom logging within your application code, writing log messages to a temporary stage. Periodically download and analyze these log files using external tools.
C) Log all application events directly to Snowflake tables using stored procedures. Analyze these tables periodically using SQL queries to identify trends and anomalies.
D) Integrate with a third-party monitoring service (e.g., Datadog, New Relic) by sending application metrics and logs via HTTP endpoints. Configure alerts and dashboards in the monitoring service.
E) Utilize Snowflake's Information Schema views (e.g., 'QUERY_HISTORY', to track query performance and resource usage. Correlate this data with application-specific events using custom logging.

3. A software company, 'Datalnsights', is developing a Snowflake Native Application that requires restricted access to a source data table in the consumer's account. Datalnsights wants to ensure that only the application can access the data, and the consumer cannot directly query it. What is the MOST secure and recommended approach Datalnsights should use within their application package to grant access?

A) Granting the ' USAGE privilege on the database and schema containing the source data table directly to the application role.
B) Exposing the table directly through the application's setup script using 'GRANT SELECT ON TABLE TO APPLICATION ROLE app_role' .
C) Granting 'SELECT privilege directly on the source data table to the application role.
D) Creating a secure view on top of the source data table and granting 'SELECT privilege to the application role on the view.
E) Using a secure UDF within the application to access the source data table, ensuring data masking and redaction, with only the UDF being granted SELECT privileges on the table.

4. As a Native App Provider, you've identified a performance bottleneck in a query against a table within your application's container due to an inefficient join. The query is part of a view exposed to consumers. Which of the following actions would be MOST effective in improving the query performance while minimizing disruption to consumers?

A) Rewrite the query in the view definition to use a more efficient join algorithm (e.g., using hints). Consumers will automatically benefit from the improved performance.
B) Create a search optimization policy on columns used in the 'WHERE' clause in the view. This does not require any changes from the consumers.
C) Add a 'CLUSTER BY clause to the underlying table based on the join keys. Consumers will automatically benefit from improved query performance without any changes on their end.
D) Create a materialized view in place of the existing view, pre-computing the join results. This will require consumers to update their queries to use the new materialized view name.
E) Implement a scheduled task to regularly update the statistics of the table involved in the join. This will help the query optimizer make better decisions, and consumers will see improved performance gradually.

5. You are developing a Snowflake Native Application that uses Streamlit for its user interface. The application needs to access a custom Python module named 'my_module' which resides within your application package. You have correctly packaged the module. However, when running the Streamlit application, you encounter an 'ImportError: No module named What is the most likely reason for this error and how can you resolve it?

A) The 'my_module' is not located in the correct directory structure within the application package. Ensure it's placed in the 'src' directory (or the directory specified in 'package-name' in 'setup.py') and the directory structure mirrors the package structure required for import.
B) The correct handler is not specified in the 'manifest.ymr file.
C) The Streamlit application is not aware of the application package's Python environment. You need to set the environment variable within the Streamlit application to point to the directory containing 'my_module'.
D) The 'my_module' is not included in the file for your application package. Add it to the 'packages' list in 'setup.py'.
E) Streamlit does not support custom Python modules within Snowflake Native Applications. You must use only built-in Python modules or those available through Anaconda.

Solutions: