Snowflake Certification Practice Test

For high cardinality columns, how is the clustering key ideally defined?

1. By the column directly

2. Using an expression on the column

3. With default settings only

4. Using a different column

The correct answer is: Using an expression on the column

Defining a clustering key using an expression on the column is particularly beneficial for high cardinality columns. High cardinality refers to columns with a large number of unique values, which can make the organization and retrieval of data more complex. By using an expression, you can create a clustering key that optimally organizes the data in a way that reflects how it will be queried. For example, if the data contains timestamp values, applying an expression that extracts only the date part can help in clustering the data so that queries focused on a specific date range can be executed efficiently. This approach allows for a more effective data distribution across the storage and retrieval process, enhancing performance and ensuring faster query response times. In contrast, defining the clustering key just by the column directly may not take full advantage of the uniqueness and distribution that an expression can leverage. Default settings or using a different column may not align with the specific query patterns you anticipate, leading to inefficient data organization. Thus, using an expression enables a more tailored approach to managing high cardinality data effectively.