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Answer: Automate the conversion process with an AWS Glue ETL job triggered by Lambda for each new .csv file in S3.
The correct answer is D. Using an AWS Glue extract, transform, and load (ETL) job to convert the .csv files to Parquet format leverages Glue's built-in capabilities for data transformation, which is both scalable and efficient. By triggering this ETL job with an AWS Lambda function upon each S3 PUT event, the process automates the file conversion with minimal operational overhead. This approach handles large data volumes effectively and is more suitable for handling the size and frequency of .csv files described in the scenario compared to other options.
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How can a company efficiently convert large .csv files to Parquet format in S3 with minimal operational overhead?
A
Use AWS Lambda to automatically convert uploaded .csv files to Parquet upon each S3 event.
B
Invoke an Apache Spark job via AWS Lambda for each .csv file upload to perform the conversion to Parquet format.
C
Set up AWS Glue with a crawler and scheduled Lambda function using Amazon Athena to periodically convert .csv files to Parquet.
D
Automate the conversion process with an AWS Glue ETL job triggered by Lambda for each new .csv file in S3.
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