DEA-C02 Performance Optimization Practice Question
When analyzing a Query Profile, which indicator most strongly suggests that 'Partition Pruning' is performing effectively?
⚠ Common exam trap
Many students mistakenly look at query duration or bytes spilled instead of micro-partition metrics when specifically asked to evaluate the effectiveness of partition 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
✓
Low partitions scanned compared to total partitions.
Partition pruning is the process where Snowflake skips scanning micro-partitions that cannot possibly contain the data requested by the query. A low 'Partitions scanned' count relative to the total 'Partitions total' is the most direct indicator that the pruning process is working. This is highly efficient as it avoids I/O operations for data that is not relevant to the query's filters, leading to faster execution times.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
High bytes scanned relative to bytes total.
Why it's wrong here
High bytes scanned indicates that a large portion of the data is being read from storage. This is the opposite of effective partition pruning. If pruning were effective, the number of bytes scanned would be significantly lower than the total bytes available in the table.
- ✓
Low partitions scanned compared to total partitions.
Why this is correct
Effective partition pruning means the query engine can identify and ignore irrelevant micro-partitions. Seeing a low number of partitions scanned compared to the total available count in the table is the primary metric indicating that the filtering logic is successfully narrowing the data access scope.
- ✗
High network transfer metrics in the profile.
Why it's wrong here
High network transfer suggests data is being moved between nodes to perform joins or aggregations, not that partitions are being pruned. Network metrics are unrelated to the effectiveness of partition pruning, which occurs during the initial data retrieval phase from persistent storage.
- ✗
The presence of a 'Join' operator in the query profile.
Why it's wrong here
The presence of a join operator is a structural component of the query plan. It tells you nothing about whether the underlying tables are being pruned effectively. Joins are executed after the data has been retrieved, and pruning happens during the retrieval phase itself.
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.