Which query metric can be used to monitor the health of a large table?
Which query metric can be used to monitor the health of a large table?
The key metric for monitoring the “health” of a large table in Snowflake is clustering depth. Clustering depth measures the average number of micro‑partition overlaps for the specified clustering key (or any set of columns), and a lower value indicates more effective clustering and thus better query pruning and performance. Tracking clustering depth over time as DML operations occur helps you detect when a table’s physical data layout degrades and may require reclustering.