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Question 114 - DP-203 discussion

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You have an Azure Stream Analytics job that receives clickstream data from an Azure event hub. You need to define a query in the Stream Analytics job. The query must meet the following requirements:

Count the number of clicks within each 10-second window based on the country of a visitor. Ensure that each click is NOT counted more than once. How should you define the Query?

A.
SELECT Country, Avg(*) AS AverageFROM ClickStream TIMESTAMP BY CreatedAtGROUP BY Country, SlidingWindow(second, 10)
Answers
A.
SELECT Country, Avg(*) AS AverageFROM ClickStream TIMESTAMP BY CreatedAtGROUP BY Country, SlidingWindow(second, 10)
B.
SELECT Country, Count(*) AS CountFROM ClickStream TIMESTAMP BY CreatedAtGROUP BY Country, TumblingWindow(second, 10)
Answers
B.
SELECT Country, Count(*) AS CountFROM ClickStream TIMESTAMP BY CreatedAtGROUP BY Country, TumblingWindow(second, 10)
C.
SELECT Country, Avg(*) AS AverageFROM ClickStream TIMESTAMP BY CreatedAtGROUP BY Country, HoppingWindow(second, 10, 2)
Answers
C.
SELECT Country, Avg(*) AS AverageFROM ClickStream TIMESTAMP BY CreatedAtGROUP BY Country, HoppingWindow(second, 10, 2)
D.
SELECT Country, Count(*) AS CountFROM ClickStream TIMESTAMP BY CreatedAtGROUP BY Country, SessionWindow(second, 5, 10)
Answers
D.
SELECT Country, Count(*) AS CountFROM ClickStream TIMESTAMP BY CreatedAtGROUP BY Country, SessionWindow(second, 5, 10)
Suggested answer: B

Explanation:

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. Example:

Incorrect Answers:

A: Sliding windows, unlike Tumbling or Hopping windows, output events only for points in time when the content of the window actually changes. In other words, when an event enters or exits the window. Every window has at least one event, like in the case of Hopping windows, events can belong to more than one sliding window. C: 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. To make a Hopping window the same as a Tumbling window, specify the hop size to be the same as the window size. D: Session windows group events that arrive at similar times, filtering out periods of time where there is no data.

Reference:

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

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asked 02/10/2024
Jonas Weimar
45 questions
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