A Data Engineer has a table with no clustering key defined. The Engineer wants to analyze the distribution of micro-partitions by using system functions. To identify the best clustering key for the…

Question

Options

• AAn error saying Invalid clustering key or table table1 is not clustered
• BNotes with suggestions on how to make the clustering more efficient
• CAn error saying The table name must be enclosed by double quotation marks
• DA histogram depicting the distribution of overlap depth for each micro-partition in the table

• A
  97% (28)
• D
  3% (1)

Explanation

SYSTEM$CLUSTERING_INFORMATION requires a clustering key to already be defined on the table - without one, Snowflake has no reference point for analyzing micro-partition distribution, so it returns an error indicating the table is not clustered (option A). Option B is wrong because Snowflake doesn't offer proactive clustering suggestions through this function - that kind of advisory output doesn't exist in this context. Option C is wrong because the syntax shown (single-quoted string argument) is perfectly valid; double quotes are used for object identifiers in SQL, not for string arguments to system functions. Option D describes output that this function would return - specifically, JSON containing overlap depth and clustering depth metrics - but only when a valid clustering key is already in place; without one, execution fails before any output is produced.

Memory tip: Think of SYSTEM$CLUSTERING_INFORMATION as a report card for an existing clustering key - if no key exists, there's nothing to grade, and Snowflake throws an error rather than guessing what to analyze.

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