AWS Certified Data Engineer Associate DEA-C01 Practice Question
An organization loads transactional CSV files every hour into an AWS data lake on Amazon S3. The data engineer must run an ELT process that performs complex conditional updates and iterative aggregations directly inside the data warehouse by using a SQL script with loops and variables. Which AWS service should the engineer use to execute this script?
Amazon Redshift supports stored procedures written in PL/pgSQL, which allow control-flow statements such as loops, conditional logic, and the use of variables. This lets engineers embed complex procedural SQL directly in the data warehouse for ELT workloads. Amazon EMR can run Hive or Spark code but would require separate cluster resources and does not execute procedural SQL inside the warehouse. Amazon Athena executes declarative SQL queries only; it does not support procedural extensions like loops. AWS Glue jobs run Python or Scala scripts that operate outside the database, not SQL scripts executed within the warehouse itself.
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What are stored procedures in Amazon Redshift?
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How does PL/pgSQL differ from regular SQL?
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Why can’t Amazon Athena execute procedural SQL?
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What is PL/pgSQL and how does it enable procedural SQL in Amazon Redshift?
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Why doesn't Amazon Athena support procedural SQL?
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What are the differences between ELT and ETL, and how does Amazon Redshift support ELT?
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AWS Certified Data Engineer Associate DEA-C01
Data Operations and Support
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