How should you complete the GROUP BY clause to meet the Streaming Analytics requirements?

How should you complete the GROUP BY clause to meet the Streaming Analytics requirements?
A . GROUP BY HoppingWindow(Second, 60, 30)
B. GROUP BY TumblingWindow(Second, 30)
C. GROUP BY SlidingWindow(Second, 30)
D. GROUP BY SessionWindow(Second, 30, 60)

View Answer

Answer: B

Explanation:

Scenario: You plan to use a 30-second period to calculate the average temperature reading of the sensors.

Tumbling window functions are used to segment a data stream into distinct time segments and perform a function against them, such as the example below. The key differentiators of a Tumbling window are that they repeat, do not overlap, and an event cannot belong to more than one tumbling window.

InAnswers:

A: Hopping window functions hop forward in time by a fixed period. It may be easy to think of them as Tumbling windows that can overlap, so events can belong to more than one Hopping window result set.

Reference: https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-window-functions