ARA-C01 Performance Optimization Practice Question
A Snowflake architect is analyzing a query that performs a large aggregation over a fact table with billions of rows. The query profile shows that the aggregation step is spilling to local disk, and the warehouse is a 2XL multi-cluster warehouse with 4 clusters. The architect wants to reduce the spilling and improve performance. Which action is most likely to achieve this?
⚠ Common exam trap
Many exam-takers confuse concurrency scaling (adding clusters) with scaling up for per-query performance, and assuming QAS can fix any performance issue.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Scale up the warehouse to a larger size to provide more memory per node.
Spilling to local disk during aggregation indicates that the query's working set exceeds the available memory per node. Scaling up the warehouse increases memory per node, allowing the aggregation to be processed in memory and reducing spilling. Adding clusters or enabling QAS does not address the per-query memory limitation.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase the number of clusters in the multi-cluster warehouse to 8.
Why it's wrong here
Adding more clusters increases concurrency for multiple queries but does not increase the memory or compute resources available to a single query. The aggregation spilling is due to insufficient memory per node for the query's working set. More clusters will not help a single query; they only allow more queries to run concurrently.
- ✗
Reduce the size of the warehouse to a smaller size to decrease spilling.
Why it's wrong here
Reducing warehouse size decreases the compute and memory resources per node, which would likely worsen spilling. A smaller warehouse has less memory to hold intermediate aggregation results, leading to more disk spilling and slower performance. This is counterproductive.
- ✓
Scale up the warehouse to a larger size to provide more memory per node.
Why this is correct
Scaling up the warehouse increases the compute and memory resources per node. A larger warehouse, such as a 3XL or 4XL, provides more memory for each node to hold intermediate aggregation results, reducing the need to spill to disk. This directly addresses the spilling issue and can significantly improve query performance.
- ✗
Enable the Query Acceleration Service to offload the aggregation.
Why it's wrong here
Query Acceleration Service (QAS) can offload portions of a query to shared compute resources, but it is primarily designed for scan-heavy queries and may not be effective for a large aggregation that is spilling. QAS does not increase the memory available for the aggregation step itself. Scaling up the warehouse is a more direct solution.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Snowflake exam blueprint
This ARA-C01 practice question is part of Courseiva's free Snowflake certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the ARA-C01 exam.