Crucial Exams

AWS Certified Data Engineer Associate DEA-C01 Practice Question

Your company ingests daily CSV files into an S3 data lake, runs an AWS Glue Spark job to denormalize the data, and then loads the result into an Amazon Redshift table that has a primary key on order_id. Duplicate order_id values occasionally appear in the source data and cause the Redshift load to fail. You must add an automated step to the existing Glue workflow that verifies the order_id column contains only unique values and stops the workflow if the rule is violated. Which approach satisfies these requirements with minimal custom code?

  • Create an AWS Glue Data Quality ruleset that uses an IsUnique rule on the order_id column and configure the evaluation action to fail the workflow when the rule fails.

  • Turn on AWS Glue job bookmarks so previously processed rows are skipped and duplicates are automatically removed during the next job run.

  • Enable versioning on the S3 bucket so duplicate files are stored as separate object versions, ensuring the downstream load receives only the latest data.

  • Use AWS Database Migration Service with a full-load task followed by validation to compare S3 data with Redshift and detect any duplicate records before loading.

AWS Certified Data Engineer Associate DEA-C01
Data Operations and Support
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