PDE Designing Data Processing Systems Practice Question
An online gaming company runs a Dataflow streaming pipeline that aggregates player actions into per-session metrics. Sessions are defined by a gap duration of 30 minutes of inactivity, and the pipeline must emit final session results even when a session's events arrive out of order by up to 10 minutes. Late data beyond that window can be dropped. Which combination of Beam concepts should the pipeline use?
⚠ Common exam trap
The trap here is treating the 30-minute gap as a fixed window length, when in session windows the gap is an inactivity threshold that merges windows rather than a fixed time bucket.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Session windows with a 30-minute gap, an allowed lateness of 10 minutes, and a trigger that fires after the watermark passes the end of the window.
Session windows are the only window type that models inactivity gaps, and combining a 30-minute gap with 10 minutes of allowed lateness keeps state open long enough for out-of-order events while dropping anything later. A watermark-based trigger emits the final result once the window is considered complete.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Fixed windows of 30 minutes with the default trigger and allowed lateness of zero.
Why it's wrong here
Fixed windows divide the stream on aligned time boundaries and do not model inactivity gaps, so a session that spans a boundary would be split incorrectly. With allowed lateness of zero, any event arriving after the watermark passes is discarded, which contradicts the requirement to tolerate out-of-order events for up to 10 minutes.
- ✗
Sliding windows of 30 minutes with a one-minute period and an early trigger firing every minute.
Why it's wrong here
Sliding windows produce overlapping aggregates on a fixed period and do not represent sessions separated by inactivity. Early per-minute firings would emit speculative results rather than final session metrics, and the overlapping windows would double-count player actions, so the output would not represent distinct sessions as required.
- ✓
Session windows with a 30-minute gap, an allowed lateness of 10 minutes, and a trigger that fires after the watermark passes the end of the window.
Why this is correct
Session windows merge based on inactivity gaps, so a 30-minute gap duration models the session definition exactly. Setting allowed lateness to 10 minutes keeps window state alive so out-of-order events within that bound are still incorporated, and firing on the watermark produces final results once the window closes, which matches the emit-final-results requirement.
- ✗
Global window with a repeated element-count trigger and a discard accumulation mode.
Why it's wrong here
A global window with a count trigger groups elements by number rather than by inactivity, so session boundaries would be arbitrary and unrelated to the 30-minute gap rule. Discarding mode also drops previous panes, so the emitted values would not be cumulative session metrics, and there is no mechanism here to bound late data by ten minutes.
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