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Snowflake NAS-C01 Exam Syllabus Topics:

Snowflake SnowPro Specialty - Native Apps Sample Questions:

1. A Snowflake Native Application is designed to process customer data using a series of stored procedures. One of the stored procedures, process data', requires access to a stage named 'customer stage' in the consumer's account to load dat a. The application role 'app_role' is intended to manage all access within the application. However, the procedure fails with a permission error during testing in the consumer environment. Which of the following combination of steps is required to fix the problem?

A) Grant 'USAGE privilege on the database and schema containing 'customer_stage' to the 'app_role', and grant 'READ privilege on 'customer_stage' to the app_role' .
B) The stored procedure needs to be defined with 'EXECUTE AS CALLER rights to assume the privileges of the role executing the procedure.
C) Grant 'USAGE privilege on the database and schema containing 'customer_stage' to the 'app_role', and create a new role in the consumer account, grant 'READ on the 'customer_stage' to this new role, then grant this new role to 'app_role' .
D) Grant 'READ and ' WRITE privilege on 'customer_stage' directly to the provider account.
E) Grant 'USAGE privilege on the database and schema containing 'customer_stage' to the provider account, and grant privilege on 'customer_stage' to the 'app_role' .

2. You are troubleshooting an issue where a Snowflake Native Application's Scala UDF, 'process_data' , is sporadically failing with an 'OutOfMemoryError'. The UDF processes large XML files. You need to identify the cause and implement a solution. Which strategies are most appropriate for diagnosing and resolving this issue within the constraints of a Snowflake Native Application?

A) Increase the warehouse size for the consumer's account. This provides more memory to the UDF execution environment.
B) Modify the 'process_data' UDF to stream the XML file instead of loading the entire file into memory at once. Use a streaming XML parser to process the data incrementally.
C) Implement caching mechanisms within the UDF to reuse previously processed XML data, reducing the need to load and parse the same data repeatedly.
D) Break down the large XML files into smaller chunks before processing them with the UDF. This reduces the memory footprint of each individual UDF execution. Implement a system to orchestrate processing chunks.
E) Use a memory profiler to analyze the UDF's memory usage. Identify memory leaks or inefficient data structures that contribute to the 'OutOfMemoryErroN.

3. You are building a Snowflake Native Application that provides a data transformation service. You want to allow consumers to configure certain aspects of the transformation pipeline (e.g., the name of the target table, specific transformation logic). What are the recommended approach(es) to allow consumers to customize the application's behavior without directly modifying the application code?

A) Expose parameters within the setup script and stored procedures that consumers can set during application installation or execution.
B) Implement a configuration table within the application's schema that consumers can update with their desired settings. The application code reads these settings at runtime.
C) Include default configurations within a file on the external stage, which consumers are expected to download, modify, and then upload back as a different file for the application to load.
D) Require consumers to fork the application's repository and modify the SQL code directly.
E) Utilize Snowflake's Secure UDFs (User-Defined Functions) and allow consumers to provide their own UDFs as configuration.

4. You're designing a Snowflake Native Application that leverages Snowpark Container Services (SPCS) and you are creating a CI/CD pipeline for deploying your application to multiple Snowflake regions. As part of the pipeline, you want to automate the creation of a Compute Pool. Which of the following approaches represents the MOST robust and repeatable method for creating the Compute Pool across all regions, considering factors like consistency and potential differences in available instance families?

A) Manually create the Compute Pool in each region using the Snowflake web interface, ensuring the parameters are identical across all instances.
B) Compute Pools created are global objects, so the pool automatically exists across all regions.
C) Use a Snowflake Script (SnowSQL) to create the Compute Pool, hardcoding the instance family and other parameters directly into the script.
D) Use a Snowflake Script (SnowSQL) to create the Compute Pool, retrieving the available instance families dynamically using 'SYSTEM$GET_CP POLICY' and selecting the appropriate instance family based on regional availability. Store common configurations in environment variables.
E) Create a Compute Pool in one region and then clone it to all other regions using the 'CREATE CLONE syntax.

5. A Native App provider has released a new version of their application. After installation, some consumers report encountering 'SQL compilation errors' when using certain features that rely on Java UDFs. The provider has thoroughly tested the application and cannot reproduce the error in their development environment. What are the MOST LIKELY causes of this issue and how can the provider systematically troubleshoot and resolve it? (Select TWO)

A) The Java UDFs are encountering data type mismatches due to differences in regional settings or data formats between the provider's and consumer's environments. The provider should enforce strict data validation and type conversion within the UDFs.
B) The consumer's Snowflake account has insufficient compute resources to execute the Java UDFs. The provider should instruct the consumer to upgrade their virtual warehouse size.
C) Consumer-side firewall rules are blocking access to external resources used by the Java UDF. The provider should thoroughly document the necessary network configurations for consumers.
D) The provider's development environment is using a newer version of the Snowflake Java runtime than the consumer's environment. The provider should downgrade their development environment to match the oldest supported version and re-test the application.
E) The Java UDFs are using external libraries that are not compatible with the consumer's Snowflake environment or are missing entirely. The provider should explicitly declare all dependencies in the application manifest and ensure they are properly packaged and deployed.

Solutions: