Databricks Certified Data Engineer - Associate
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A data analysis team has noticed that their Databricks SQL queries are running too slowly when connected to their always-on SQL endpoint. They claim that this issue is present when many members of the team are running small queries simultaneously. They ask the data engineering team for help. The data engineering team notices that each of the team's queries uses the same SQL endpoint.
Which of the following approaches can the data engineering team use to improve the latency of the team's queries?
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KKeng
A
They can increase the cluster size of the SQL endpoint.
B
They can increase the maximum bound of the SQL endpoint's scaling range.
C
They can turn on the Auto Stop feature for the SQL endpoint.
D
They can turn on the Serverless feature for the SQL endpoint.
E
They can turn on the Serverless feature for the SQL endpoint and change the Spot Instance Policy to "Reliability Optimized."
Explanation:
Correct Answer: A
Explanation:
When many users are running small queries simultaneously on a SQL endpoint, the database can become overloaded, causing slow query execution times. By increasing the cluster size of the SQL endpoint, the database can handle more simultaneous queries, resulting in faster query execution times.
Why other options are incorrect:
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B. Increasing the maximum bound of the SQL endpoint's scaling range: This would allow the endpoint to scale to larger clusters when needed, but the issue is that the current cluster size is insufficient for the concurrent workload. Increasing the cluster size directly (option A) is more appropriate.
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C. Turning on the Auto Stop feature: This feature automatically stops the SQL endpoint after a period of inactivity to save costs. It doesn't improve performance for active workloads and might actually cause delays when queries need to restart the endpoint.
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D. Turning on the Serverless feature: While Serverless SQL endpoints can provide better resource management, the core issue here is insufficient compute resources for concurrent queries. Serverless alone doesn't solve the resource capacity problem.
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E. Turning on Serverless feature and changing Spot Instance Policy: Similar to option D, this doesn't address the fundamental issue of insufficient compute capacity for concurrent small queries. The Spot Instance Policy affects cost optimization, not performance scaling for concurrent workloads.
Key Takeaway: When dealing with performance issues due to many concurrent small queries on a SQL endpoint, increasing the cluster size provides more compute resources to handle the concurrent workload, directly addressing the latency problem.
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