最新的Snowflake SnowPro Specialty - Native Apps - NAS-C01免費考試真題

A. Employing a Stored Procedure owned by the application role that queries the table in the provider account, and allowing access to the procedure via API integration.

B. Granting the CONSUMPTION usage privilege on the provider account database to the consumer account, and then granting SELECT on the specific table to a role that the app assumes.

C. Creating a Snowflake Secure UDF that queries the table within the provider account and exposing the UDF to the consumer account through a package.

D. Granting direct SELECT access to the consumer role on the table in the provider account, ensuring to revoke access after the app is installed.

E. Creating a Snowflake Secure View on the table in the provider account and sharing this view with the consumer account using Data Sharing.

A. Store all usage data in a single table and rely on Snowflake's automatic clustering to handle performance.

B. Implement a data retention policy to automatically purge older usage data that is no longer needed.

C. Use clustering keys on columns commonly used in queries, such as timestamp and consumer account ID. Consider data compression options if available.

D. Partition the usage data table by consumer account ID to isolate data from different consumers.

E. Create separate tables for each consumer account to store their usage data.

A. Implement Role-Based Access Control (RBAC) within the application, granting only the necessary privileges to each role.

B. Use Snowflake Secrets to securely store and manage any API keys or credentials required by the application.

C. Implement Dynamic Data Masking on sensitive columns within the application's data container.

D. Grant the APPLICATION ROLE access to all tables within the consumer's Snowflake account.

E. Disable network policies on the application container to allow unrestricted access to external resources.

A. Increase the warehouse size for the consumer's account. This provides more memory to the UDF execution environment.

B. Implement caching mechanisms within the UDF to reuse previously processed XML data, reducing the need to load and parse the same data repeatedly.

C. 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.

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.

A. 1. Create a new APPLICATION role for beta testers. 2. Grant USAGE privilege on version v2.0 to the beta testers APPLICATION role. 3. Update the default version of the application package to v2.0.

B. 1. Create a new APPLICATION role for beta testers. 2. Grant USAGE privilege on version v2.0 to the beta testers APPLICATION role. 3. Instruct beta testers to manually specify VERSION = 'v2.0' when creating their application instances.

C. 1. Create a new APPLICATION role for beta testers. 2. Grant USAGE privilege on the application package to the beta testers APPLICATION role. 3. Grant USAGE privilege on version v2.0 to the beta testers APPLICATION role. 4. Update the default version of the application package to v2.0.

D. 1. Instruct consumers to use the 'ALTER APPLICATION' command to upgrade to v2.0. 2. Monitor consumer feedback on the upgraded version.

E. 1. Create a dedicated APPLICATION role for the application. 2. Grant OWNERSHIP on the application package to the application's APPLICATION role. 3. Update the default version of the application package to v2.0.

A. Use on the provider's account to establish a secure connection and directly debug the provider's stored procedures.

B. Raise a support ticket with the provider through the Snowflake Marketplace. Include example queries, input data, and the expected vs. actual results to facilitate their debugging process. Further, Query data using different warehouse sizes to see if concurrency is a factor.

C. Contact Snowflake Support and provide them with a detailed description of the issue and relevant query examples. Snowflake Support can access the provider's environment and investigate.

D. Examine the 'INSTALLATION INFORMATION' view in the application's database to check for provider-published error messages or status updates related to data quality issues. Use queries to identify patterns in the inconsistent results.

E. Utilize the 'DEBUG' procedure exposed by the application (if any) to step through the risk calculation logic with specific input values.

A. Package all SQL scripts and UDFs into a single, large SQL file and execute it during installation.

B. Use a deployment tool like Flyway or Liquibase to manage database schema changes and versioning, integrating it into your application's setup script.

C. Rely exclusively on Snowflake's built-in version control features (if available), which automatically manage schema changes.

D. Manually execute each SQL script and UDF creation statement in the consumer's Snowflake environment.

E. Store SQL Scripts and UDFs external to the application, providing instructions to the consumers to manually download and install.

A. Define the external functions in the application manifest, specifying the API integration object used for secure communication and authentication.

B. Grant the 'USAGE privilege on the API integration object to the application role that will be calling the external functions within the application package. This is done through the application setup script.

C. Implement robust error handling and logging within the application code to capture any issues related to external function calls, including authentication errors, network connectivity problems, and data transformation failures.

D. Create a network rule in the application package that whitelists the IP addresses or hostnames of the external function endpoints. Ensure that the application manifest includes the property set to 'true' and references the network rule.

E. No explicit configuration is required within the application package; external functions are automatically accessible once defined in the developer's Snowflake account.

A. Release patches as separate SQL scripts that consumers must manually apply to their installed application instances using the ACCOUNTADMIN role.

B. Use versioning, creating a new version of the application package for each set of changes, and instruct consumers to manually update their application instances to the latest version.

C. Completely rebuild the application package for each release, pushing a new application to Snowflake Marketplace, forcing users to uninstall and reinstall. This guarantees a clean state but may cause disruptions.

D. Implement in-place upgrades to the application package every time a bug fix is released, granting UPDATE privileges on the underlying data tables to the application.

E. Use versioning, leveraging application roles and grants to control access to specific application versions. Employ automated rollout procedures to progressively expose new versions to consumers using application lifecycle management features.

A. Write a Python script leveraging the Snowflake Connector for Python to upload the files using multi-threading or asynchronous operations.

B. Compress the files into a single ZIP archive before uploading using the 'PUT' command.

C. Use the Snowflake Visual Studio Code (VS Code) extension's built-in file upload feature, which automatically handles parallel uploads.

D. Use the 'PUT ' command with the 'PARALLEL' option enabled in SnowSQL.

E. Utilize Snowflake's internal staging using 'PUT command on Internal stage for smaller file and external stage for larger file and then copy the larger file from external to internal by referencing file URL.

A. Use a 'MERGE statement to selectively update only changed rows, while ignoring existing ones.

B.

C. Leverage Snowflake's 'TRANSACTIONAL_REPLICATION' to replicate the operations to minimize data loss in between failures.

D. Wrap the 'df.write' operation in a retry mechanism with exponential backoff to handle intermittent network errors.

E. Create a temporary table, write the transformed data to the temporary table, and then atomically rename the temporary table to the original table name.

A. Bundle the Python library as a ZIP file along with your application code. When creating the function using 'CREATE FUNCTION' , specify the ZIP file as part of the 'IMPORTS' clause. Snowflake automatically extracts and makes the library available to the function.

B. Upload the Python library as a stage object and reference it in the 'manifest.ymr file using the 'artifacts' section. Snowflake will automatically include it in the application package and make it available during runtime using the 'IMPORT' statement in the handler code.

C. Combine options B and C. Use the Anaconda channel integration when possible, and for custom or unavailable packages, use the ZIP file import method for individual functions. Prioritize Anaconda for easier dependency management.

D. Upload the Python library using the 'PUT' command and explicitly reference it in the 'manifest.ymr under the 'artifacts' section, pointing to the internal stage location. Use the 'IMPORT statement within your stored procedure or UDF handler code to make the library available during execution.

E. Use the Anaconda channel integration. Specify the required package in the 'manifest.ymr file, and Snowflake automatically downloads and installs the library during application installation. This only works for packages available through Anaconda.

A. Include directly within your application package's source code and call its functions from within your application's procedures. Grant necessary privileges on the procedures to the consumer's role, ensuring to only expose the procedures and never the python source.

B. Store 'data_transform.py' as an internal stage file and read it dynamically into your application's Python code at runtime.

C. Publish 'data_transform.py' as a public Python package on Anaconda and have consumers install it in their Snowflake environment.

D. Package 'data_transform.py' as a user-defined function (UDF) and grant 'USAGE privilege on the UDF to the consumer's role.

E. Embed the contents of 'data_transform.py' directly within the application's stored procedure code as a multi-line string.

A. Store sensitive data in an internal stage within the provider account. Create a stored procedure that reads data from the stage, aggregates and de-identifies it, and writes the results to a shareable table. The consumer application can query the shareable table.

B. Store sensitive data in a table within the provider account. Create a user-defined function (UDF) that aggregates and de-identifies the data. Share the table and the UDF with the consumer account through a share. The consumer application can then use the UDF to query the data.

C. Store sensitive data in a secured view within the provider account. Grant the consumer account usage privileges on this secured view. Create a setup script using 'CREATE APPLICATION ROLE and 'GRANT to give the consumer's application role access to the secured view.

D. Store sensitive data in a table within the provider account. Create a stored procedure that aggregates and de-identifies the data, writing the results to a new table. Share this new, aggregated table with the consumer account via a data share.

E. Store sensitive data in a table within the provider account. Use dynamic data masking policies to de-identify the data when accessed by the consumer account. Share the underlying table directly with the consumer account through a share.