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.
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Billhardy
1 week, 5 days ago