Answer: The use of pruning

The question asks how Snowflake improves performance for queries that filter out significant data. Option B (The use of pruning) is correct because Snowflake uses micro-partition pruning to eliminate irrelevant data early in query processing, which is highly effective when queries filter out large amounts of data. This avoids scanning unnecessary micro-partitions, reducing I/O and improving performance. Option A (The use of indexing) is incorrect as Snowflake does not use traditional indexes; it relies on micro-partitions and metadata. Option C (The use of TableScan) is incorrect as TableScan refers to full table scans, which are inefficient for filtered queries. Option D (By increasing the number of partitions scanned) is incorrect because scanning more partitions would degrade performance, not improve it. The community discussion unanimously supports B with 100% consensus and upvotes, reinforcing that pruning is the key optimization.

Author: LeetQuiz Editorial Team