Databricks Certified Data Engineer - Associate
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A data engineer wants to schedule their Databricks SQL dashboard to refresh every hour, but they only want the associated SQL endpoint to be running when it is necessary. The dashboard has multiple queries on multiple datasets associated with it. The data that feeds the dashboard is automatically processed using a Databricks Job.
Which of the following approaches can the data engineer use to minimize the total running time of the SQL endpoint used in the refresh schedule of their dashboard?
Real Exam
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KKeng
A
They can turn on the Auto Stop feature for the SQL endpoint.
B
They can ensure the dashboard’s SQL endpoint is not one of the included query’s SQL endpoint.
C
They can reduce the cluster size of the SQL endpoint.
D
They can ensure the dashboard’s SQL endpoint matches each of the queries’ SQL endpoints.
E
They can set up the dashboard’s SQL endpoint to be serverless.
Explanation:
Explanation
The correct answer is A. They can turn on the Auto Stop feature for the SQL endpoint.
Why this is correct:
-
Auto Stop Feature: This feature automatically stops the SQL endpoint after a period of inactivity, which directly addresses the requirement to minimize total running time. When the dashboard refreshes every hour, the SQL endpoint will start for the refresh and then automatically stop after the query execution completes.
-
Cost Optimization: Auto Stop ensures the SQL endpoint only runs when actively processing queries, reducing compute costs and resource consumption.
-
Serverless vs. Auto Stop: While serverless endpoints (option E) also provide on-demand scaling, they don't necessarily minimize total running time in the same way. Serverless endpoints are always available but scale to zero when idle, while Auto Stop actually stops the endpoint completely.
Why other options are incorrect:
- B: Ensuring the dashboard's SQL endpoint is not one of the included query's SQL endpoint doesn't minimize running time; it might actually increase complexity without addressing the core requirement.
- C: Reducing cluster size affects performance, not running time. Smaller clusters might take longer to execute queries, potentially increasing total running time.
- D: Matching SQL endpoints doesn't minimize running time; it ensures consistency but doesn't address the need to run only when necessary.
- E: While serverless endpoints provide on-demand scaling, they don't explicitly minimize total running time in the same way as Auto Stop. Serverless endpoints are designed for availability and automatic scaling, not specifically for minimizing runtime.
Key Takeaway:
The Auto Stop feature is specifically designed for scenarios where SQL endpoints are needed intermittently, allowing them to automatically stop when idle and restart when needed, which perfectly matches the requirement of minimizing total running time while supporting hourly dashboard refreshes.
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