DEA-C02 Performance Optimization Practice Question
Which of the following is the best practice for using the query profile to identify performance bottlenecks?
⚠ Common exam trap
Candidates often waste time optimizing low-impact operators or early-stage filtering instead of focusing on the 'heavy' operators that actually contribute the highest percentage to the overall query execution time.
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
✓
Start by identifying the operator with the highest time contribution.
The most effective approach is to focus on the 'heavy' operators, which are the parts of the query plan consuming the most time or resources. By analyzing the Query Profile from the top-down, an engineer can isolate where the processing is stalling. This targeted analysis is crucial for performance tuning, as it prevents wasting time on minor optimizations and ensures that efforts are directed toward the root causes of latency, such as spilling or high I/O.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Only analyze queries that take longer than one hour.
Why it's wrong here
Waiting for queries to run for an hour is inefficient. Many queries that perform poorly can be identified and optimized long before they reach that threshold. Any query that consumes a significant portion of the warehouse's budget or impacts user experience should be analyzed for potential performance improvements.
- ✓
Start by identifying the operator with the highest time contribution.
Why this is correct
The operator with the highest time contribution is the most significant bottleneck. By focusing on this node first, you address the primary source of latency. This approach ensures that your optimization efforts have the greatest possible impact on the total query duration and overall warehouse credit consumption.
- ✗
Ignore spilling metrics if the query eventually finishes.
Why it's wrong here
Spilling is a major performance indicator that the query is under-resourced. Even if a query completes, it is performing sub-optimally. Ignoring spilling means you are missing an opportunity to improve query speed and cost-efficiency by either resizing the warehouse or optimizing the data access pattern.
- ✗
Focus primarily on the number of partitions scanned.
Why it's wrong here
While partition scanning is important, it is only one piece of the puzzle. Focusing only on this metric might lead you to ignore other critical issues like processing skew, join overhead, or local disk I/O, which could be the actual causes of the slow query performance.
About these practice questions
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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 DEA-C02 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 DEA-C02 exam.