Question

A data engineer manages a 12 TB events table that is frequently queried with filters on an event_date column. Query performance has degraded over time because new data arrives continuously and rows for the same date end up scattered across many micro-partitions. The engineer wants Snowflake to automatically reorganize the table's data so that partitions are better co-located by event_date, improving pruning for date-range queries. Which action should the engineer take?

Accepted Answer

Define a clustering key on event_date so Automatic Clustering maintains co-location as new data loads

Answer

Increase the virtual warehouse size so more micro-partitions can be scanned in parallel

Answer

Enable multi-cluster scaling on the warehouse to distribute the date-range queries across clusters

Answer

Recreate the table with a smaller micro-partition size to reduce the number of partitions scanned