SAA-C03 · Question #572
SAA-C03 Question #572: Real Exam Question with Answer & Explanation
The correct answer is A: Create an Amazon S3 bucket. Configure DynamoDB to export to the bucket on a regular. DynamoDB export to Amazon S3 (via point-in-time exports or table backups) "does not consume read capacity" and has no impact on table performance. Once data is in S3, Amazon Redshift can ingest efficiently with COPY from S3, which is the standard, parallel, high-throughput load p
Question
A company needs a solution to integrate transaction data from several Amazon DynamoDB tables into an existing Amazon Redshift data warehouse. The solution must maintain the provisioned throughput of DynamoDB. Which solution will meet these requirements with the LEAST operational overhead?
Options
- ACreate an Amazon S3 bucket. Configure DynamoDB to export to the bucket on a regular
- BUse an Amazon Redshift COPY command to read directly from each DynamoDB table.
- CCreate an Amazon S3 bucket. Configure an AWS Lambda function to read from the DynamoDB
- DUse Amazon Athena Federated Query with a DynamoDB connector and an Amazon Redshift
Explanation
DynamoDB export to Amazon S3 (via point-in-time exports or table backups) "does not consume read capacity" and has no impact on table performance. Once data is in S3, Amazon Redshift can ingest efficiently with COPY from S3, which is the standard, parallel, high-throughput load path with minimal management. Direct COPY from DynamoDB (B) performs a table scan that can consume provisioned throughput, risking throttling. Building Lambda pipelines (C) adds custom code and scheduling overhead. Athena federated queries (D) are ad hoc analytics, not optimized for bulk, recurring warehouse loads. Therefore, exporting to S3 and loading with Redshift COPY maintains DynamoDB throughput and minimizes operational burden.
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