AWS Certified Data Engineer Associate DEA-C01 Practice Question

A data engineer wrote an AWS Lambda function that is triggered when a nightly 3-GB CSV file is uploaded to an Amazon S3 bucket. The function reads the file, keeps only three columns, and then loads the filtered data into Amazon Redshift. Most invocations exceed the 512-MB memory setting and hit the 15-minute timeout. The team wants to keep the serverless architecture and fix the failures with minimal refactoring. Which solution will meet these requirements?

  • Modify the Lambda code to use Amazon S3 Select so that only the needed columns are streamed into the function before loading into Amazon Redshift.

  • Replace the Lambda trigger with an Amazon Redshift COPY command that is scheduled nightly with Amazon EventBridge.

  • Split the CSV into 50-MB chunks with a separate script and rely on multipart upload completion events to invoke the same Lambda function for each chunk.

  • Increase the function's memory to 10,240 MB and extend the timeout to 30 minutes in the Lambda console.

AWS Certified Data Engineer Associate DEA-C01
Data Ingestion and Transformation
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