AWS Certified Data Engineer Associate DEA-C01 Practice Question
Your company maintains a Microsoft SQL Server 2019 database on premises. A weekly AWS Glue Spark job must extract data, transform it, and upload results to Amazon S3. Security policy prohibits JDBC; the connection must use an ODBC DSN. Which approach minimizes ongoing administration while meeting the requirement?
Launch an Amazon EMR cluster, install the SQL Server ODBC driver with a bootstrap action, run the Spark transformation as an EMR step, and terminate the cluster after the job completes.
Create an AWS Glue connection of type JDBC that points to the SQL Server endpoint and reference the connection in the job.
Use AWS Database Migration Service to replicate the on-premises database into Amazon RDS for SQL Server and have the Glue job read from the replica with the default driver.
Build a custom Docker image that includes the SQL Server ODBC driver and DSN configuration, store the image in Amazon ECR, and assign the image to the AWS Glue job.
AWS Glue native connections and connectors rely on JDBC drivers, so they cannot satisfy a policy that mandates ODBC only. By packaging the required SQL Server ODBC driver, unixODBC libraries, and a pre-configured DSN inside a custom Docker image stored in Amazon ECR, the Glue job can load those components at runtime and establish an ODBC session to the on-premises database. This keeps the solution fully managed and serverless-no clusters to patch or decommission. Launching an Amazon EMR cluster with the driver would work technically, but the cluster adds operational overhead that the question asks to avoid. Replicating the source with AWS DMS or creating a Glue JDBC connection both violate the stated requirement that the original database must be reached via ODBC.
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AWS Certified Data Engineer Associate DEA-C01
Data Ingestion and Transformation
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