Crucial Exams

AWS Certified Data Engineer Associate DEA-C01 Practice Question

A data engineering team loads a daily fact file into an internal Amazon Redshift table. The upstream system will start delivering Parquet files in Amazon S3 and might add extra columns at any time. The team must make the new data queryable in Redshift without manual schema updates or table recreation, while keeping performance high and storage costs low. Which solution meets these requirements?

  • Run an ALTER TABLE statement to add every new column after it appears, then reload the data into a rebuilt internal table created with UNLOAD and COPY.

  • Transform each Parquet file back to CSV with an AWS Glue job, then load the result into the internal table with COPY.

  • Continue using the COPY command into the existing internal table and specify IGNOREHEADER to skip any new columns that are added.

  • Create a Redshift Spectrum external table that points to the Parquet files in S3 and schedule an AWS Glue crawler to update the Data Catalog table when new columns appear.

AWS Certified Data Engineer Associate DEA-C01
Data Store Management
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