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A data engineer wants to schedule their Databricks SQL dashboard to refresh once per day, but they only want the associated SQL endpoint to be running when it is necessary.
Which approach can the data engineer use to minimize the total running time of the SQL endpoint used in the refresh schedule of their dashboard?
A
They can ensure the dashboard's SQL endpoint matches each of the queries' SQL endpoints.
B
They can set up the dashboard's SQL endpoint to be serverless.
C
They can turn on the Auto Stop feature for the SQL endpoint.
D
They can ensure the dashboard's SQL endpoint is not one of the included query's SQL endpoint.
Explanation:
The correct answer is C - They can turn on the Auto Stop feature for the SQL endpoint.
Auto Stop Feature: This feature automatically stops a SQL endpoint after a period of inactivity, which helps minimize running time and costs.
Use Case Fit: Since the dashboard only needs to refresh once per day, the SQL endpoint can be stopped when not in use. The Auto Stop feature will automatically stop the endpoint after the scheduled refresh completes, and it will automatically start again when the next scheduled refresh occurs.
Cost Optimization: This approach directly addresses the requirement to minimize total running time while ensuring the endpoint is available when needed for the daily refresh.
A: Ensuring the dashboard's SQL endpoint matches each query's SQL endpoints doesn't minimize running time - it just ensures consistency but doesn't control when the endpoint runs.
B: Setting up the SQL endpoint to be serverless doesn't directly minimize running time. Serverless endpoints still incur costs while running, though they may have different billing models.
D: Ensuring the dashboard's SQL endpoint is not one of the included query's SQL endpoint doesn't help minimize running time and could actually increase complexity without addressing the core requirement.
The Auto Stop feature is specifically designed for scenarios where SQL endpoints are only needed periodically, allowing them to automatically stop when idle and restart when needed, thus optimizing costs and resource utilization.