SOL-C01 Question #146: Real Exam Question with Answer & Explanation

Question

A data team is designing a data pipeline that loads data from S3 into Snowflake. The raw data in S3 is compressed using gzip and stored in multiple files. They want to use a Snowflake virtual warehouse to perform the data loading. Which of the following COPY INTO command options would be MOST appropriate to optimize the data loading process?

Options

• ASpecify 'ON_ERROR = CONTINUE in the COPY INTO command to skip any files with errors.
• BUse the 'VALIDATION_MODE = RETURN ERRORS parameter to identify any issues within the
• CUtilize 'MATCH BY COLUMN NAME = CASE INSENSITIVE so that the command is robust to case
• DSpecify 'FILE FORMAT = (TYPE = CSV COMPRESSION = GZIP)' in the COPY INTO command to
• ESet the 'MAX FILE_SIZE parameter to a smaller value to force Snowflake to process files in

Explanation

ERROR = CONTINUE (A) skips errors but doesn't address decompression. 'VALIDATION MODE' (B) is helpful for debugging but doesn't directly optimize the loading process. (C) can ease development but has nothing to do with compression. Specifying = (TYPE = CSV COMPRESSION = GZIP)' (D) allows Snowflake to handle gzip decompression automatically. 'MAX FILE_SIZE (E) can be useful in certain scenarios but is not related to compressed files directly. Splitting the warehouse is not a COPY INTO option, but rather a high-level architecture

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