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 approach 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.
Explanation:
Explanation
When many team members are running small queries simultaneously on the same SQL endpoint, the issue is likely related to concurrency limitations. SQL endpoints in Databricks have scaling ranges that determine how many clusters can be spawned to handle concurrent queries.
Let's analyze each option:
A. They can increase the cluster size of the SQL endpoint.
- This would increase the compute power of individual clusters, but wouldn't necessarily help with concurrent query execution. Larger clusters handle individual queries faster but don't increase the number of queries that can run simultaneously.
B. They can increase the maximum bound of the SQL endpoint's scaling range. ✅ CORRECT
- This is the correct approach. By increasing the maximum bound of the scaling range, you allow the SQL endpoint to spawn more clusters to handle concurrent queries. This directly addresses the issue of many team members running queries simultaneously.
- SQL endpoints can scale out (add more clusters) to handle increased concurrency, and the scaling range determines the minimum and maximum number of clusters that can be created.
C. They can turn on the Auto Stop feature for the SQL endpoint.
- Auto Stop automatically stops the SQL endpoint after a period of inactivity to save costs. This would actually make the problem worse because queries would experience cold start delays when the endpoint needs to restart.
D. They can turn on the Serverless feature for the SQL endpoint.
- Serverless SQL endpoints automatically scale compute resources, but this feature is about resource provisioning, not specifically about increasing concurrency limits. While Serverless can help with resource management, the specific issue described (many concurrent small queries) is best addressed by adjusting the scaling range.
Key Concept: SQL endpoint scaling ranges control how many clusters can be created to handle concurrent workloads. When many users run queries simultaneously, increasing the maximum bound allows more clusters to be created, reducing contention and improving query latency.
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