ARA-C01 Performance Optimization Practice Question
Which system function should an architect use to evaluate the clustering health of a table and determine if the current clustering key is effectively organizing the data into distinct micro-partitions?
⚠ Common exam trap
Candidates frequently suggest querying the metadata tables (like TABLE_STORAGE_METRICS) instead of using the dedicated system function, which provides a more direct calculation of clustering depth and overlap.
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
✓
SYSTEM$CLUSTERING_INFORMATION
The SYSTEM$CLUSTERING_INFORMATION function provides detailed metrics about a table's clustering, including the average clustering depth and the overlap between micro-partitions. A high clustering depth indicates that the clustering key is not effective or that the table has become disorganized over time, requiring re-clustering or a new key.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
SYSTEM$ESTIMATE_SEARCH_OPTIMIZATION_COSTS
Why it's wrong here
This function is used to estimate the credits required to maintain the Search Optimization Service on a specific table or column. It does not provide any information about the clustering depth or the effectiveness of the micro-partition organization for existing clustering keys in the database schema.
- ✗
SYSTEM$CLUSTERING_DEPTH
Why it's wrong here
While 'clustering depth' is a concept in Snowflake, the actual function name is SYSTEM$CLUSTERING_INFORMATION. There is no standalone function called SYSTEM$CLUSTERING_DEPTH. Architects must use the broader information function to retrieve the depth along with other diagnostic metrics like the overlap histogram and constant partition counts.
- ✓
SYSTEM$CLUSTERING_INFORMATION
Why this is correct
This is the correct function for analyzing clustering health. It returns a JSON object containing the total partition count, average depth, and a histogram of overlapping partitions. This data is essential for an architect to decide whether to add, change, or remove a clustering key to improve query performance.
- ✗
SYSTEM$QUERY_PROFILE_ANALYZER
Why it's wrong here
There is no system function with this exact name in Snowflake. Query analysis is typically performed through the web interface's Query Profile tab or by querying account usage views. It is not a dedicated system function used to measure the physical organization of data within micro-partitions on disk.
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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
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