ARA-C01 Snowflake Architecture Practice Question
Exhibit
SELECT "partitions_scanned", "partitions_total"
FROM TABLE(INFORMATION_SCHEMA.QUERY_PROFILE('01af34...'))
WHERE "operator_type" = 'TableScan';Refer to the exhibit. A query profile shows that 'partitions_scanned' is 5,000 while 'partitions_total' is 5,000 for a specific TableScan operator. What architectural issue does this indicate, and what is the recommended solution?
⚠ Common exam trap
Candidates often suggest scaling up the warehouse size when partitions scanned equals total partitions, failing to realize that compute power cannot fix a missing partition pruning strategy.
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
✓
Data is poorly clustered for the query filters; define a Cluster Key.
When the number of scanned partitions equals the total partitions, it means that no pruning occurred, and Snowflake performed a full table scan. Architecturally, this usually happens because the query filter does not align with the way data is organized in micro-partitions. Defining a Cluster Key on the columns used in the filter is the standard architectural fix to enable efficient pruning.
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; increase it to improve the scan speed.
Why it's wrong here
Increasing the warehouse size will make a full table scan finish faster because more nodes are reading the data in parallel. However, it does not solve the underlying architectural problem of zero pruning. The goal of an architect should be to minimize the data read, which is achieved through pruning, not just making the scan faster.
- ✗
The query is hitting the metadata cache; no action is required.
Why it's wrong here
If a query were hitting the metadata cache or result cache, the profile would show that zero partitions were scanned, or it would indicate a 'Result Cache' hit. Scanning all 5,000 partitions is the opposite of a cache hit; it indicates that every single micro-partition had to be opened and read from the storage layer to satisfy the query.
- ✓
Data is poorly clustered for the query filters; define a Cluster Key.
Why this is correct
Zero pruning indicates that the min/max values for the filtered columns overlap across all micro-partitions, or the filters are not being applied effectively. By defining a Cluster Key, Snowflake will reorganize the data so that values are grouped together, allowing the Cloud Services layer to prune the majority of partitions based on their metadata.
- ✗
The table is a Transient table; convert it to a Permanent table.
Why it's wrong here
The table type (Transient vs. Permanent) has no impact on query pruning or the efficiency of table scans. Both table types use the same micro-partitioning architecture and metadata-driven pruning. The difference between them is strictly related to data retention (Time Travel and Fail-safe) and storage costs, not query execution performance or pruning capabilities.
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.