Sales data is aggregated with Athena from S3, and users repeatedly explore the same dashboard.
Refresh the data hourly while avoiding the same aggregation query for every interaction.
Which architecture is most appropriate?
Load the dataset into Amazon QuickSight SPICE and refresh it on a schedule so interactive dashboards reuse an analysis-optimized copy.
Detailed explanation
SPICE keeps analysis data in memory, so repeated dashboard interactions do not run the same Athena queries while scheduled refreshes preserve the required freshness.
SPICE keeps analysis data in memory, so repeated dashboard interactions do not run the same Athena queries while scheduled refreshes preserve the required freshness.
DNS health checks do not cache query results or visualization data.
DNS health checks do not cache query results or visualization data.
Per-user execution and file generation add operational overhead and inconsistent response times.
Per-user execution and file generation add operational overhead and inconsistent response times.
Archive storage is not a low-latency source for interactive visualization.
Archive storage is not a low-latency source for interactive visualization.
Check official documentation
Compare the following points with the official documentation.
Amazon QuickSight SPICE and scheduled refreshの公式説明を確認する。
What to confirm
可視化層のキャッシュとデータレイクの原本更新を分けて考えられる。
Key points
- Amazon QuickSight
- SPICE
- Scheduled refresh
Notes
- Environment:
- Confirm current behavior in the official SAA-C03 guide and AWS service documentation.
Foundation review
Visualization response
An analysis copy avoids repeating the same aggregation for every interaction.
Freshness versus speed
Compare refresh interval and query load against the required data freshness.