AWS Certified Data Engineer Associate DEA-C01 Practice Question
An AWS Glue ETL job launches several AWS Lambda functions that create and transform hundreds of 100-MB intermediary Parquet files. The files must be shared across concurrent function invocations and retained for downstream steps executed minutes later. Which approach will meet these requirements with the LEAST operational overhead while remaining within Lambda service quotas?
Configure the Lambda function's ephemeral /tmp storage to 10 GB and write the intermediary files there so each invocation can read files created by other invocations.
Use AWS DataSync inside the function to mount an Amazon S3 bucket as a local POSIX file system for reading and writing the intermediary files.
Attach an Amazon EBS volume to the Lambda function by initiating an AWS Systems Manager session and store the files on that volume.
Create an Amazon EFS file system, configure an access point, and attach it to the Lambda function by specifying the file system ARN and mount path.
AWS Lambda can mount an Amazon Elastic File System (Amazon EFS) access point directly into the Lambda runtime. The file system provides a shared, low-latency POSIX directory that is accessible to every concurrent invocation of the function and persists across cold starts, satisfying both the sharing and durability needs. Configuring an EFS mount requires only that the function run in the same VPC and that security groups allow NFS traffic, so operational overhead is minimal.
Increasing ephemeral /tmp storage does not allow different containers to see each other's data and is still limited to 10 GB per instance. Lambda cannot mount Amazon S3 through AWS DataSync, and Amazon EBS volumes cannot be attached to Lambda functions. Therefore, mounting an EFS access point is the only option that meets all functional and service-quota constraints.
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AWS Certified Data Engineer Associate DEA-C01
Data Ingestion and Transformation
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