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AWS Certified Data Engineer - Associate
A data engineer must run a basic Python ETL script against a dataset of approximately 8 GB with the lowest possible compute footprint. The team wants to avoid managing Apache Spark clusters and does not need horizontal scaling. Which AWS Glue authoring approach best fits these requirements?
Explanation
Python shell jobs are designed for running basic ETL scripts written in Python. These jobs run on a single machine, and are better suited for
Python shell is intended for basic ETL jobs with small or medium-sized datasets (up to approximately 10 GB).
In an AWS Glue Studio visual job, a data engineer needs to combine rows from two separate data sources that share the same schema into a single dataset. Which built-in managed transform should be used?
Explanation
Union : Combine rows from more than one data source that have the same schema.
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