Databricks-Certified-Data-Engineer-Associate Free Practice Test

An engineering manager wants to monitor the performance of a recent project using a Databricks SQL query. For the first week following the project’s release, the manager wants the query results to be updated every minute. However, the manager is concerned that the compute resources used for the query will be left running and cost the organization a lot of money beyond the first week of the project’s release.
Which of the following approaches can the engineering team use to ensure the query does not cost the organization any money beyond the first week of the project’s release?

1. A. They can set a limit to the number of DBUs that are consumed by the SQL Endpoint.
2. B. They can set the query’s refresh schedule to end after a certain number of refreshes.
3. C. They cannot ensure the query does not cost the organization money beyond the first week of the project’s release.
4. D. They can set a limit to the number of individuals that are able to manage the query’s refresh schedule.
5. E. They can set the query’s refresh schedule to end on a certain date in the query scheduler.

Correct Answer: E
If a dashboard is configured for automatic updates, it has a Scheduled button at the top, rather than a Schedule button. To stop automatically updating the dashboard and remove its subscriptions:
Click Scheduled.
In the Refresh every drop-down, select Never.
Click Save. The Scheduled button label changes to Schedule. Source:https://learn.microsoft.com/en-us/azure/databricks/sql/user/dashboards/

Which of the following is hosted completely in the control plane of the classic Databricks architecture?

1. A. Worker node
2. B. JDBC data source
3. C. Databricks web application
4. D. Databricks Filesystem
5. E. Driver node

Correct Answer: C
In the classic Databricks architecture, the control plane includes components like the Databricks web application, the Databricks REST API, and the Databricks Workspace. These components are responsible for managing and controlling the Databricks environment, including cluster provisioning, notebook management, access control, and job scheduling. The other options, such as worker nodes, JDBC data sources, Databricks Filesystem (DBFS), and driver nodes, are typically part of the data plane or the execution environment, which is separate from the control plane. Worker nodes are responsible for executing tasks and computations, JDBC data sources are used to connect to external databases, DBFS is a distributed file system for data storage, and driver nodes are responsible for coordinating the execution of Spark jobs.