CSV logs are added to S3 daily and must be queried efficiently with Athena.
Use columnar compression so queries can read only the required columns.
Which processing approach is most appropriate?
Run an AWS Glue ETL job that converts CSV to compressed, partitioned Parquet.
Detailed explanation
Glue can transform, compress, and partition S3 data so Athena scans less data.
Glue can transform, compress, and partition S3 data so Athena scans less data.
Versioning preserves object versions but does not change file format or compression.
Versioning preserves object versions but does not change file format or compression.
IAM controls access permissions and does not transform stored data.
IAM controls access permissions and does not transform stored data.
CloudTrail records AWS API activity and does not transform data files.
CloudTrail records AWS API activity and does not transform data files.
Check official documentation
Compare the following points with the official documentation.
AWS GlueのETL、Parquet、圧縮、Athenaの列プルーニングの公式説明を確認する。
What to confirm
認証・監査・保存形式変換の役割を区別できる。
Key points
- AWS Glue ETL
- CSV
- Parquet
- Columnar format
Notes
- Environment: AWS公式DEA-C01試験ガイドと各サービスの公式ドキュメントの確認
- Confirm current AWS service behavior in the official DEA-C01 documentation.
Foundation review
Scan reduction
Column pruning and compression reduce Athena data scanned when queries select a subset of columns.
Output contract
Partition keys, schema, codec, and failed-record handling should be defined for downstream queries.