AWS Certified Data Engineer Associate DEA-C01 Practice Question
An AWS Glue job writes hourly click-stream data to staging.clicks in an Amazon Redshift cluster. A data engineer must deduplicate the rows, merge into prod.f_clicks, then refresh statistics. To keep the workflow simple, the engineer wants one CALL that completes the entire ETL atomically, with no further commits from the scheduler.
Which SQL pattern meets these requirements?
Call three separate stored procedures: one to deduplicate, one to merge, and one to analyze, from the orchestration workflow.
Create or replace a PL/pgSQL stored procedure that starts with BEGIN and ends with END; but omits any COMMIT or ROLLBACK statements.
Embed COMMIT; after each DML statement inside a single stored procedure to avoid long-running transactions.
Keep the logic in the workflow and execute individual UPDATE, DELETE, and ANALYZE statements over the Data API instead of using a stored procedure.
In Amazon Redshift, a stored procedure automatically runs inside a single implicit transaction. As long as the procedure itself does not issue an explicit COMMIT or ROLLBACK, every statement inside the body is committed (or rolled back) together when the CALL returns. Wrapping the business logic in a PL/pgSQL block that begins with CREATE OR REPLACE PROCEDURE … LANGUAGE plpgsql AS $$ BEGIN and ends with END; $$ keeps the job atomic. Using COMMIT statements inside the procedure, issuing individual UPDATE/DELETE statements from the scheduler, or running multiple CALL commands would each introduce separate transactions and defeat the single-commit requirement.
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AWS Certified Data Engineer Associate DEA-C01
Data Ingestion and Transformation
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