Exam Certified Data Engineer Associate topic 1 question 130 discussion

The scenario describes: Many small SQL queries being run simultaneously. A shared, always-on SQL endpoint. Performance degradation due to concurrent usage, not necessarily large queries. Why Option B is correct: SQL Endpoints in Databricks SQL support scaling ranges, which define how many concurrent clusters (or compute resources) can be spun up to handle query loads. By increasing the maximum bound, Databricks can add more clusters in parallel, allowing more users' queries to run concurrently with lower latency. This directly addresses the query queuing or slowdowns caused by multiple simultaneous users.

It's always on, no need for serverless to speed up start-up.

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.

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.

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:

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.