COF-C03 Practice Question: Performance Optimization, Querying, and Transformation
A data engineer notices that a query performing a large aggregation is spilling to remote disk. The warehouse is a 2XL multi-cluster warehouse with maximum clusters set to 4. The engineer wants to reduce spilling and improve performance without increasing the warehouse size. Which action should the engineer take?
⚠ Common exam trap
The trap here is assuming that adding more clusters or enabling query acceleration will help a single query that is spilling, when in fact those features address concurrency or specific query patterns, not memory-intensive operations.
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
✓
Rewrite the query to use a smaller aggregation or break it into stages.
Remote disk spilling occurs when the aggregation operation cannot fit its intermediate results in memory. The most direct way to reduce spilling without increasing warehouse size is to reduce the memory demand of the query itself. Rewriting the query to perform smaller aggregations or breaking it into stages can lower the peak memory usage, allowing the operation to complete within the available memory. This addresses the underlying issue rather than trying to work around it with additional resources.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Rewrite the query to use a smaller aggregation or break it into stages.
Why this is correct
Spilling to remote disk indicates that the aggregation operation requires more memory than available on the warehouse nodes. Rewriting the query to reduce the memory footprint, such as by pre-aggregating data in stages or using smaller groups, can decrease the memory required and avoid spilling. This directly addresses the root cause without increasing warehouse size.
- ✗
Increase the maximum cluster count to 8.
Why it's wrong here
Increasing the maximum cluster count allows more concurrent queries to run, but it does not increase the memory available to a single query. Spilling occurs when a single query's operations exceed the memory of a warehouse node. Adding clusters does not help a single query that is already spilling; it only helps with concurrency. This action would not reduce spilling for the problematic query.
- ✗
Enable the query acceleration service for the warehouse.
Why it's wrong here
The query acceleration service can offload portions of a query to shared compute resources, but it is primarily designed for queries with large scans and filters, not for aggregations that spill. It may not reduce spilling caused by memory-intensive aggregation operations. It is not a direct solution for the described issue.
- ✗
Add a clustering key on the group by columns.
Why it's wrong here
Clustering can improve pruning and reduce I/O for filtered queries, but it does not reduce the memory required for aggregation. The aggregation still needs to process all rows, and spilling is due to memory constraints during the aggregation. Clustering would not alleviate the spilling issue; it might even add overhead if not carefully chosen.
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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 COF-C03 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 COF-C03 exam.