DP-203 Develop data processing Practice Question
You are designing a streaming job in Azure Stream Analytics. The job needs to count the number of events per device type every 10 seconds. The input is from Event Hubs. Which query should you use?
⚠ Common exam trap
Candidates often confuse HoppingWindow with TumblingWindow, thinking a hop size of 1 second still produces 10-second intervals, but HoppingWindow emits results at every hop, not at the window duration, leading to incorrect output frequency.
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
✓
SELECT DeviceType, COUNT(*) FROM Input GROUP BY DeviceType, TumblingWindow(second, 10)
A TumblingWindow(second, 10) produces non-overlapping, fixed-size 10-second windows, which is exactly what is needed to count events per device type every 10 seconds. The GROUP BY clause groups by DeviceType and the window, ensuring each device type gets its own count per window. This query meets the requirement without overlapping or sliding behavior.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
SELECT DeviceType, COUNT(*) FROM Input GROUP BY DeviceType, SessionWindow(second, 10, 30)
Why it's wrong here
Session window is based on inactivity, not fixed time.
- ✓
SELECT DeviceType, COUNT(*) FROM Input GROUP BY DeviceType, TumblingWindow(second, 10)
Why this is correct
Tumbling window outputs exactly every 10 seconds.
- ✗
SELECT DeviceType, COUNT(*) FROM Input GROUP BY DeviceType, HoppingWindow(second, 10, 1)
Why it's wrong here
Hopping window with hop 1 produces results every second, not every 10 seconds.
- ✗
SELECT DeviceType, COUNT(*) FROM Input GROUP BY DeviceType, SlidingWindow(second, 10)
Why it's wrong here
Sliding window outputs for each event, not on a fixed interval.
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