
Explanation:
Pruning efficiency in Snowflake refers to how effectively the query optimizer eliminates unnecessary micro-partitions from scanning, which directly impacts query performance. The PARTITIONS_SCANNED metric shows how many micro-partitions were actually accessed during query execution, while PARTITIONS_TOTAL represents the total number of micro-partitions in the scanned tables. The ratio of PARTITIONS_SCANNED to PARTITIONS_TOTAL indicates pruning effectiveness - a lower ratio means better pruning. The community discussion confirms this with 100% consensus on BE, explaining that 'pruning efficiency = partitions_scanned / partitions_total ratio'. Other options like EXECUTION_TIME, COMPILATION_TIME, and TOTAL_ELAPSED_TIME measure query performance timing but don't directly assess pruning efficiency.
Which columns in the QUERY_HISTORY view in the Account Usage schema can be used to evaluate the pruning effectiveness of a query? (Choose two.)
A
EXECUTION_TIME
B
PARTITIONS_TOTAL
C
COMPILATION_TIME
D
TOTAL_ELAPSED_TIME
E
PARTITIONS_SCANNED
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