Databricks Certified Data Engineer - Associate

Explanation

When Databricks SQL queries are running too slowly when submitted to a non-running SQL endpoint, the main issue is that the endpoint needs to start up (cold start) before processing queries. This startup time contributes significantly to the overall query execution time.

Let's analyze each option:

A. Turn on Serverless feature and change Spot Instance Policy to "Reliability Optimized"

• Serverless SQL endpoints can help with cold starts, but changing the Spot Instance Policy to "Reliability Optimized" is more about cost optimization and reliability than reducing startup time.

B. Turn on the Auto Stop feature for the SQL endpoint

• Auto Stop automatically stops the endpoint after a period of inactivity to save costs. This would actually make the problem worse because it would cause more frequent cold starts.

C. Increase the cluster size of the SQL endpoint (CORRECT)

• Increasing the cluster size provides more compute resources, which can significantly reduce query execution time. Larger clusters have more processing power and memory, allowing queries to run faster. This directly addresses the performance issue.

D. Turn on the Serverless feature for the SQL endpoint

• While Serverless endpoints can help with cold starts by providing faster provisioning, it's not the most direct solution for improving query performance once the endpoint is running.

E. Increase the maximum bound of the SQL endpoint's scaling range

• This allows the endpoint to scale to larger sizes when needed, but doesn't guarantee faster performance for individual queries, especially during cold starts.

Key Insight: The question specifically mentions queries are slow when submitted to a non-running SQL endpoint. While cold start is part of the problem, increasing cluster size provides more compute resources that can process queries faster once the endpoint is running, which is the most direct solution to improve query performance.