Snowflake Certification Practice Test

When should database designers consider using Clustering Keys?

1. When tables are very small

2. When tables are large and provide sufficient filtering

3. Only when data is not changing

4. When tables are in a single micro-partition

The correct answer is: When tables are large and provide sufficient filtering

Clustering Keys are particularly beneficial for large tables where effective filtering can lead to improved query performance. When tables are large, the distribution of data across micro-partitions becomes significant, potentially resulting in uneven data organization. This can lead to inefficiencies when querying, as specific data might be spread across a vast number of micro-partitions. Using Clustering Keys allows database designers to define the columns that are most frequently filtered or sorted on, thus promoting better organization of the data within the micro-partitions based on these keys. This means that, when executing queries, the system can more effectively scan the necessary partitions, leading to faster query response times and reduced load on the system. In contrast, utilizing Clustering Keys on very small tables does not yield the same benefits, as the data is inherently manageable, and query performance is already optimized without additional clustering. Similarly, the consideration of data change and the number of micro-partitions is less critical for creating Clustering Keys since they are meant to organize data for optimal query performance rather than just being applied based on data volatility or partition count.