A data engineer has a one-time need to read Apache Parquet objects in an S3 bucket and extract only a single column. Which option achieves this with minimal operational overhead?
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Correct answer: Use S3 Select to write a SQL SELECT statement to retrieve the required column from the S3 objects..
Why this is the answer
S3 Select is the most efficient option for this one-time task because it allows you to retrieve a subset of data directly from an S3 object using SQL expressions, minimizing data transfer and processing. This significantly reduces operational overhead compared to other services. The other options introduce unnecessary complexity or overhead for a single-column extraction: AWS Lambda with pandas requires writing and deploying code, and loading the entire Parquet file into memory, which is inefficient for a single column. AWS Glue DataBrew is a data preparation service designed for more complex transformations and data cleaning, not a simple column extraction. AWS Glue Crawler and Amazon Athena are powerful for querying structured data at scale, but for a one-time, single-column extraction from Parquet, setting up a crawler and Athena table adds overhead that S3 Select avoids.
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