SAA-C03 · Question #319
A company runs an online order management system on AWS. The company stores order and inventory data for the previous 5 years in an Amazon Aurora MySQL database. The company deletes inventory data…
The correct answer is B. Use the SELECT INTO OUTFILE S3 query on the Aurora database to export the data to Amazon. The SELECT INTO OUTFILE S3 feature allows you to export Amazon Aurora MySQL data directly to Amazon S3 with minimal operational overhead. This method is efficient and cost- effective for archiving historical data. You can configure S3 Lifecycle rules to transition the exported…
Question
A company runs an online order management system on AWS. The company stores order and inventory data for the previous 5 years in an Amazon Aurora MySQL database. The company deletes inventory data after 5 years. The company wants to optimize costs to archive data. Which solution will meet this requirement?
Options
- ACreate an AWS Glue crawler to export data to Amazon S3. Create an AWS Lambda function to
- BUse the SELECT INTO OUTFILE S3 query on the Aurora database to export the data to Amazon
- CCreate an AWS Glue DataBrew Job to migrate data from Aurora to Amazon S3. Configure S3
- DUse the AWS Schema Conversion Tool (AWS SCT) to replicate data from Aurora to Amazon S3.
How the community answered
(50 responses)- A2% (1)
- B80% (40)
- C12% (6)
- D6% (3)
Explanation
The SELECT INTO OUTFILE S3 feature allows you to export Amazon Aurora MySQL data directly to Amazon S3 with minimal operational overhead. This method is efficient and cost- effective for archiving historical data. You can configure S3 Lifecycle rules to transition the exported data to lower-cost storage (e.g., S3 Glacier or S3 Standard-IA) and eventually delete it after 5 years. No need for additional ETL tools like Glue or DataBrew unless complex transformations are required.
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