DEA-C01 · Question #258
A company processes 500 GB of audience and advertising data daily, storing CSV files in Amazon S3 with schemas registered in AWS Glue Data Catalog. They need to convert these files to Apache Parquet f
The correct answer is C. Use AWS Glue workflows to run the first two processes in parallel. Ensure that the third process. AWS Glue workflows natively orchestrate multiple Glue jobs in parallel and support dependency triggers so the third job starts only after the first two finish. Glue jobs provide the required ~15 GiB memory capacity and easily convert CSV to Parquet using the Glue Data Catalog, de
Question
A company processes 500 GB of audience and advertising data daily, storing CSV files in Amazon S3 with schemas registered in AWS Glue Data Catalog. They need to convert these files to Apache Parquet format and store them in an S3 bucket. The solution requires a long-running workflow with 15 GiB memory capacity to process the data concurrently, followed by a correlation process that begins only after the first two processes complete. Which solution will meet these requirements with the LEAST operational overhead?
Options
- AUse Amazon Managed Workflows for Apache Airflow (Amazon MWAA) to orchestrate the
- BUse Amazon EMR to run each process in the workflow. Create an Amazon Simple Queue
- CUse AWS Glue workflows to run the first two processes in parallel. Ensure that the third process
- DUse AWS Step Functions to orchestrate a workflow that uses multiple AWS Lambda functions.
How the community answered
(32 responses)- A3% (1)
- B3% (1)
- C84% (27)
- D9% (3)
Explanation
AWS Glue workflows natively orchestrate multiple Glue jobs in parallel and support dependency triggers so the third job starts only after the first two finish. Glue jobs provide the required ~15 GiB memory capacity and easily convert CSV to Parquet using the Glue Data Catalog, delivering a fully managed, low-operations solution.
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