ARA-C01 Performance Optimization Practice Question
Exhibit
CLI Output: SELECT count(*) FROM sales WHERE date >= '2023-01-01' AND date <= '2023-01-31'; Profile: - Total Execution Time: 45s - Partitions Scanned: 1000 - Partitions Total: 1000
Refer to the exhibit. What is the most likely performance issue here?
⚠ Common exam trap
Candidates often assume that because a filter is present, the query should be fast, ignoring that the physical layout of the data must support that filter via pruning.
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
✓
The table is not effectively clustered by the date column.
The exhibit shows that the query scanned all 1,000 partitions despite applying a filter on a date range. This indicates that the data is not physically organized by the date column, preventing the engine from performing partition pruning. Because no partitions could be skipped, the engine was forced to scan every single micro-partition, leading to long execution times regardless of the filter's narrow range.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The warehouse is too small for the amount of data.
Why it's wrong here
While a larger warehouse might make the scan faster, the fundamental problem is that the scan is happening at all. Efficient queries should prune partitions. A small warehouse is not the cause of the scan efficiency failure; the lack of appropriate clustering is the true root of this performance issue.
- ✓
The table is not effectively clustered by the date column.
Why this is correct
When a query filters by a specific range and scans all partitions, it is a clear sign that the physical data layout does not support the query filter. By clustering the table by the date column, the engine can identify and skip partitions that fall outside the specified date range.
- ✗
The result cache is disabled.
Why it's wrong here
The result cache is enabled by default in Snowflake and cannot be disabled. If a query is slow, it is because it is performing actual compute work, not because the cache is missing. The profile clearly shows an expensive scan, which signifies that the engine is doing unnecessary data processing.
- ✗
The query is missing a search optimization index.
Why it's wrong here
Search optimization is for point lookups, not range queries. Even if an index were added, it would not assist in pruning partitions for a range filter. The correct solution for range filtering is clustering the data to allow the engine to ignore non-relevant partitions during the scan process.
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 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.