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Are you always concerned about the results in the exam?

NEW QUESTION: 1
Given the following information:

In which order should the LPARs be activated to ensure that all of them will start?
A. lpar 4 lpar 3 lpar 1 lpar 2
B. lpar 2 lpar 3 lpar 4 lpar 1
C. lpar1 lpar2 lpar3 lpar4
D. lpar2 lpar3 lpar1 lpar4
Answer: C

NEW QUESTION: 2

A. Option D
B. Option C
C. Option B
D. Option A
Answer: D

NEW QUESTION: 3
Which of the following information in a packet can be marked or re-marked?
A. IP DSCP, IP precedence, and 802.1p information
B. Any information in the packet
C. MAC address
D. IP source and destination addresses
Answer: A

NEW QUESTION: 4
How should you complete the GROUP BY clause to meet the Streaming Analytics requirements?
A. GROUP BY TumblingWindow(Second, 30)
B. GROUP BY HoppingWindow(Second, 60, 30)
C. GROUP BY SlidingWindow(Second, 30)
D. GROUP BY SessionWindow(Second, 30, 60)
Answer: A
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