Clustering depth can be used to monitor the clustering health of a large table and to decide whether a clustering key would help. True or False?

• A. True
• B. False
• C. Not applicable
• D. Only for small tables

Answer: (A)

Clustering depth is a diagnostic that shows how well a table’s data aligns with its clustering key across micro-partitions. It tells you how far the data is from being perfectly ordered by the clustering key. In practice, a low depth means the data is already well clustered and existing queries benefit from partition pruning, while a high depth indicates many rows are out of order with respect to the clustering key.

This metric is used to monitor clustering health on large tables because it provides a quantitative signal of when clustering is helping or when it’s time to recluster or introduce/adjust a clustering key. If clustering depth is unfavorable (consistently high or increasing), adding or modifying a clustering key or running a recluster can lead to more efficient pruning and faster queries. If the depth is acceptable, no clustering changes are needed.

So the statement is true: clustering depth can be used to monitor clustering health and to decide whether a clustering key would help.