Question

A retail analytics team streams point-of-sale events into Pub/Sub and processes them with a Dataflow streaming pipeline. Business users need a running total of sales revenue per store, emitted every hour on the hour, so they can compare hourly performance across the day. Events can arrive slightly out of order, and the team wants each hourly figure to reflect only the transactions that occurred within that clock hour. Which windowing and triggering configuration should the pipeline use?

Accepted Answer

Apply fixed (tumbling) windows of one hour keyed by store, with a watermark-based trigger and an allowed lateness to handle out-of-order events

Answer

Apply a global window with a processing-time trigger firing every hour, accumulating all events since the pipeline started

Answer

Apply session windows with a one-hour gap duration keyed by store so that inactive periods close each window

Answer

Apply sliding windows of one hour with a one-minute period keyed by store to continuously recompute revenue