DP-700 · Question #90
You have a Fabric workspace named EventStream1. EventStream1 outputs events to a table named Table1 in a lakehouse. The streaming data is sourced from motorway sensors and represents the speed of…
The correct answer is C. tumbling. To average car speeds from an EventStream by fixed, non-overlapping, and contiguous one-minute intervals where each event belongs to exactly one window, you should use a tumbling window function.
Question
Exhibit
Options
- Asliding
- Bhopping
- Ctumbling
- Dsession
How the community answered
(35 responses)- A3% (1)
- C91% (32)
- D6% (2)
Why each option
To average car speeds from an EventStream by fixed, non-overlapping, and contiguous one-minute intervals where each event belongs to exactly one window, you should use a tumbling window function.
A sliding window produces an output every time the window slides by a fixed interval, meaning windows can overlap, and events can belong to multiple windows.
A hopping window is a variation of a sliding window where it 'hops' forward by a specified period, meaning windows can also overlap, and events can belong to multiple windows.
A tumbling window function segments a data stream into distinct, non-overlapping, and contiguous time intervals. Each event is assigned to exactly one window, which is ideal for calculating aggregates like averages over fixed time durations, such as the specified one-minute intervals for car speeds.
A session window groups events that arrive closely together within a certain timeframe, typically used for user activity or other event sequences with varying gaps, and does not guarantee fixed, contiguous intervals.
Concept tested: EventStream tumbling window function
Source: https://learn.microsoft.com/en-us/fabric/real-time-analytics/eventstreams/eventstream-transformation-editor
Topics
Community Discussion
No community discussion yet for this question.