An upstream producer may remove columns or change types.
Detect breaking changes before implicit conversions damage downstream results.
Which quality approach is most appropriate?
Compare the incoming schema with a registered contract and reject or isolate incompatible changes before processing.
Detailed explanation
Column and type differences can be detected and routed before they break consumers.
Column and type differences can be detected and routed before they break consumers.
This destroys the historical contract and downstream expectations.
This destroys the historical contract and downstream expectations.
Automatic inference can silently accept a breaking change.
Automatic inference can silently accept a breaking change.
Storage transitions do not validate schemas.
Storage transitions do not validate schemas.
Check official documentation
Compare the following points with the official documentation.
AWS Glue Schema Registry compatibility、Data Catalog schema、schema driftの公式説明を確認する。
What to confirm
自動推測による受け入れと契約ベースのスキーマ検査の違いを説明できる。
Key points
- Schema drift
- Data contract
- Compatibility
- Type change
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
Change classification
Additions, removals, renames, and type changes have different compatibility effects.
Isolation
Keep incompatible input separate until the producer and consumer agree on a migration.