Question

A retail company streams point-of-sale transactions into a Microsoft Fabric Eventstream. The business wants only per-store total sales amounts, computed in 5-minute non-overlapping intervals, written to an Eventhouse for near real-time dashboards. Raw individual transactions must NOT be persisted to reduce storage. Which approach should you implement inside the Eventstream?

Accepted Answer

Add a Group by operator in the Eventstream event processor using a 5-minute tumbling window grouped by store, then route the aggregated output to the Eventhouse destination.

Answer

Route the raw stream directly to the Eventhouse destination and build a KQL update policy on the destination table to aggregate after ingestion.

Answer

Add a Group by operator in the Eventstream using a 5-minute hopping window with a 1-minute hop, then route the output to the Eventhouse.

Answer

Ingest the raw stream into a Lakehouse via a shortcut and use a scheduled Spark structured streaming job to aggregate every 5 minutes.