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Exam Certified Data Engineer Associate All Questions

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Exam Certified Data Engineer Associate topic 1 question 130 discussion

Actual exam question from Databricks's Certified Data Engineer Associate
Question #: 130
Topic #: 1
[All Certified Data Engineer Associate Questions]

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?

  • 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.
Show Suggested Answer Hide Answer
Suggested Answer: B 🗳️

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Jugiboss
1 month, 2 weeks ago
Selected Answer: B
It's always on, no need for serverless to speed up start-up.
upvoted 2 times
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7082935
3 months ago
Selected Answer: B
The question states that the developers are connected to their "always-on" SQL Endpoint. This means there is no startup delay. We can increase performance of many simultaneous queries by scaling out.
upvoted 2 times
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9d4d68a
3 months ago
further, A. Increase the cluster size of the SQL endpoint: While increasing the cluster size might help if the current cluster size is insufficient, it does not necessarily address the scaling needs dynamically. The SQL endpoint might still be limited by its scaling configuration. C. Turn on the Auto Stop feature: Auto Stop helps manage costs by automatically stopping the SQL endpoint when it is idle. However, it doesn't address performance issues related to simultaneous query execution and would not improve query latency directly. D. Turn on the Serverless feature: The Serverless SQL endpoint is designed for ad-hoc querying without requiring dedicated clusters. While it could help in certain scenarios, it may not be directly applicable if the issue is specifically related to high concurrency and resource contention in an always-on environment. By increasing the scaling range, the SQL endpoint can handle more concurrent queries and improve overall performance.
upvoted 1 times
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9d4d68a
3 months ago
Given the scenario where the data analysis team is experiencing slow query performance due to multiple small queries running simultaneously on the same SQL endpoint, the best approach to improve the latency of these queries is: B. They can increase the maximum bound of the SQL endpoint’s scaling range. Here’s why this approach is suitable: Increasing the maximum bound of the SQL endpoint’s scaling range allows the SQL endpoint to scale out more resources as needed. If many users are running queries simultaneously, the increased scaling range ensures that additional compute resources are available to handle the load, which can reduce query latency and improve performance. Here's why the other options are less suitable:
upvoted 1 times
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80370eb
3 months, 1 week ago
Selected Answer: D
Turning on the Serverless feature allows the SQL endpoint to scale automatically and efficiently handle a large number of small queries, improving performance and reducing latency.
upvoted 1 times
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