Many dashboards use the same daily sales aggregate.
Avoid scanning the base table for every viewer and refresh the result when source data changes.
Which approach is most appropriate?
Use a Redshift materialized view with a refresh policy and monitor its freshness and dependencies.
Detailed explanation
Archive retrieval is unsuitable for interactive dashboard queries.
Archive retrieval is unsuitable for interactive dashboard queries.
Repeated scans increase workload and response time.
Repeated scans increase workload and response time.
The aggregate is stored for reuse and can be refreshed from its source tables.
The aggregate is stored for reuse and can be refreshed from its source tables.
CloudTrail records API activity and does not cache SQL results.
CloudTrail records API activity and does not cache SQL results.
Check official documentation
Compare the following points with the official documentation.
Amazon Redshift materialized views、AUTO REFRESH、query rewriteの公式説明を確認する。
What to confirm
結果再利用と基表の毎回集計の違いを説明できる。
Key points
- Materialized view
- Refresh
- Freshness
- Query rewrite
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
Freshness versus cost
Refresh frequency should match the dashboard SLA rather than every small source change.
Dependency management
Source schema, permissions, and refresh failures affect the view's reliability.