ARA-C01 Performance Optimization Practice Question
A Snowflake architect is reviewing a query that performs a large aggregation over a fact table. The Query Profile shows that the aggregation is spilling to local disk. The warehouse is a Medium size. The architect wants to reduce or eliminate spilling to improve performance. Which action is most likely to achieve this?
⚠ Common exam trap
The trap here is assuming that clustering or Query Acceleration Service will solve spilling, when spilling is fundamentally a memory limitation that requires more memory per node.
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
✓
Increase the warehouse size to Large.
Spilling to local disk occurs when an operation requires more memory than the warehouse can provide. Increasing the warehouse size adds more memory per node, allowing the aggregation to complete in-memory and eliminating spilling. While other options might offer some benefits, they do not directly provide additional memory to the operation. Scaling up the warehouse is the most direct and effective solution for memory-intensive operations that are spilling.
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 warehouse size to Large.
Why this is correct
Increasing the warehouse size provides more memory and compute resources per node, which can reduce or eliminate spilling to local disk. A larger warehouse has more memory available for aggregation operations, allowing them to complete in-memory. This directly addresses the spilling issue shown in the Query Profile. While it increases cost, it is often the most straightforward solution for memory-intensive operations like large aggregations.
- ✗
Enable the Query Acceleration Service.
Why it's wrong here
Query Acceleration Service offloads portions of query processing to shared compute resources, which can help with scans and some aggregations, but it is not specifically designed to eliminate spilling. Spilling is a memory issue within the warehouse, and QAS does not provide additional memory to the warehouse. It may improve overall performance for certain queries, but it is not the targeted fix for spilling to local disk.
- ✗
Add a clustering key on the group-by columns.
Why it's wrong here
Clustering on group-by columns can improve pruning and reduce the amount of data scanned, but it does not directly address spilling during aggregation. Spilling occurs when the aggregation operation requires more memory than available, regardless of how much data is scanned. Clustering might reduce the data volume, but if the aggregation still exceeds memory, spilling will continue. It is not the most direct solution for this issue.
- ✗
Create a materialized view for the aggregation.
Why it's wrong here
A materialized view precomputes the aggregation, which can eliminate the need to perform it at query time. However, it does not address spilling for ad-hoc aggregations that are not covered by the view. Materialized views are best for repetitive, predictable queries. In this scenario, the architect is dealing with a specific query that is spilling; creating a materialized view might help if the query is recurrent, but it is not a general solution for spilling and adds maintenance overhead.
About these practice questions
This ARA-C01 question is part of Courseiva's 209-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
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.