SnowPro Core Certification COF-C03 Passing Score

The correct answer is D. File-level metadata of all data files in an internal or external stage .

A Snowflake directory table is associated with a stage and stores file-level metadata for files in that stage. It lets users query staged file information using SQL.

Why D is correct:

Directory tables hold metadata about staged files, such as file name, relative path, size, last modified time, and file URL information.

Example concept:

SELECT *

FROM DIRECTORY(@my_stage);

This returns metadata for files in the stage associated with the directory table.

Why the other options are incorrect:

A. Directory tables do not store metadata about views in a schema.

B. Directory tables do not store metadata about regular Snowflake tables in a schema.

C. Directory tables do not store clustering key metadata.

Official Snowflake documentation reference:

Snowflake documentation describes directory tables as objects that store file-level metadata about staged files in cloud storage.

The correct answer is A. Split the file into smaller files .

Snowflake can load files in parallel. A single very large file limits parallelism because fewer worker threads can process the load concurrently. Splitting a very large file into multiple smaller files allows Snowflake to load the files in parallel, improving performance.

Why A is correct:

For best loading performance, Snowflake recommends splitting large data files into smaller files of a recommended size range so that the load operation can be parallelized.

Why the other options are incorrect:

B. Increasing the warehouse size can sometimes help, but if the load is constrained by a single very large file, file splitting is the better optimization.

C. SIZE_LIMIT controls the maximum amount of data loaded during a COPY command. It does not improve performance for a very large file.

D. COMPRESSION = AUTO lets Snowflake detect compression type. It does not solve the lack of parallelism caused by a single large file.

Official Snowflake documentation reference:

Snowflake documentation recommends splitting large files into smaller files to increase parallelism and improve load performance.