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AWS Certified Data Engineer Associate DEA-C01 Practice Question

A data engineering team uses an AWS Lambda function written in Python to convert incoming CSV files to Apache Parquet. The function is invoked by Amazon S3 event notifications and writes the output to another bucket. During seasonal traffic, up to 3,000 objects arrive within one minute, leading to frequent cold starts, longer execution duration, and CPU starvation. The team must improve runtime performance and sustain peak throughput without modifying the application code. Which action meets these requirements MOST effectively?

  • Replace the S3 trigger with an Amazon SQS queue and set the Lambda function's reserved concurrency to 1 so that files are processed sequentially.

  • Migrate the code to an AWS Glue job that runs on a schedule every minute to batch process new files.

  • Increase the function timeout value and enable the maximum number of asynchronous invocation retry attempts.

  • Increase the function memory size and configure provisioned concurrency to match the expected peak number of parallel invocations.

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