Question 690 of 760
DP-203 Develop data processing Practice Question
You are developing a real-time data processing solution using Azure Stream Analytics. The input is an Azure Event Hubs stream with JSON data containing a 'timestamp' field. You need to output the average temperature per device every minute using a tumbling window. Which query should you use?
⚠ Common exam trap
A common mix-up: candidates confuse `SlidingWindow` or `HopWindow` with `TumblingWindow`, not realizing that only `TumblingWindow` produces non-overlapping, fixed-interval outputs required for a simple per-minute average.
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 DeviceId, AVG(Temperature) AS AvgTemp FROM Input TIMESTAMP BY Timestamp GROUP BY DeviceId, TumblingWindow(minute, 1)
A tumbling window is a fixed, non-overlapping time window that groups events into distinct time segments. Using `TumblingWindow(minute, 1)` with `TIMESTAMP BY Timestamp` ensures that the average temperature per device is computed over each one-minute interval without overlap, which matches the requirement of 'every minute'.
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 DeviceId, AVG(Temperature) AS AvgTemp FROM Input TIMESTAMP BY Timestamp GROUP BY DeviceId, SlidingWindow(minute, 1)
Why it's wrong here
Sliding window emits results when events occur within a gap, not fixed intervals.
- ✓
SELECT DeviceId, AVG(Temperature) AS AvgTemp FROM Input TIMESTAMP BY Timestamp GROUP BY DeviceId, TumblingWindow(minute, 1)
Why this is correct
Tumbling window of 1 minute produces non-overlapping windows.
- ✗
SELECT DeviceId, AVG(Temperature) AS AvgTemp FROM Input TIMESTAMP BY Timestamp GROUP BY DeviceId, SessionWindow(minute, 1, 1)
Why it's wrong here
Session window groups based on inactivity gaps.
- ✗
SELECT DeviceId, AVG(Temperature) AS AvgTemp FROM Input TIMESTAMP BY Timestamp GROUP BY DeviceId, HopWindow(minute, 1, 1)
Why it's wrong here
HopWindow with equal size and hop is same as tumbling, but the question asks for tumbling.
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Last reviewed: Jun 24, 2026
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