Which query profile statistics help determine if efficient pruning is occurring? (Choose two.)

Question

Options

• ABytes sent over network
• BPercentage scanned from cache
• CPartitions total
• DBytes spilled to local storage
• EPartitions scanned

• A
  2% (1)
• B
  6% (4)
• C
  91% (59)
• D
  2% (1)

Explanation

Pruning refers to Snowflake's ability to skip micro-partitions that cannot contain data relevant to a query. To evaluate pruning efficiency, you compare: (C) Partitions total - the total number of micro-partitions in the table, and (E) Partitions scanned - the number of micro-partitions actually read during query execution. If partitions scanned is significantly lower than partitions total, pruning is effective. If they are nearly equal, pruning is poor, often indicating a missing or ineffective clustering key. Bytes sent over the network and bytes spilled to local storage indicate data movement and memory pressure, not pruning. Percentage scanned from cache reflects cache hit rate, not pruning behavior.

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