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Exam DP-203 topic 2 question 16 discussion

Actual exam question from Microsoft's DP-203
Question #: 16
Topic #: 2
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Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
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You are designing an Azure Stream Analytics solution that will analyze Twitter data.
You need to count the tweets in each 10-second window. The solution must ensure that each tweet is counted only once.
Solution: You use a hopping window that uses a hop size of 10 seconds and a window size of 10 seconds.
Does this meet the goal?

  • A. Yes
  • B. No
Show Suggested Answer Hide Answer
Suggested Answer: A 🗳️

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Highly Voted 3 years, 8 months ago
The answer should be "Yes". Hopping window with hop size equals window size should be the same as Tumbling window.
upvoted 129 times
DataEngineer7331
2 years ago
A Tumbling Window would be correct. But as stated in the following, a hopping window can be the same as a tumbling window: "To make a Hopping window the same as a Tumbling window, specify the hop size to be the same as the window size." https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-window-functions#hopping-window
upvoted 13 times
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YipingRuan
3 years, 6 months ago
ensure that each tweet is counted only once
upvoted 22 times
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dsp17
2 years, 9 months ago
Correct Ans: B. tumbling window Read the question carefully - "The solution must ensure that each tweet is counted only once." By defination, hopping window is not non-overlapping
upvoted 8 times
strato
2 years, 9 months ago
a hopping window with equal window size to the hopping is effectively non-overlapping. If the size of the hop was smaller, sure.
upvoted 10 times
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medsimus
Highly Voted 3 years, 6 months ago
Unlike tumbling windows, hopping windows model scheduled overlapping windows. A hopping window specification consist of three parameters: the timeunit, the windowsize (how long each window lasts) and the hopsize (by how much each window moves forward relative to the previous one). Additionally, offsetsize may be used as an optional fourth parameter. Note that a tumbling window is simply a hopping window whose ‘hop’ is equal to its ‘size’.
upvoted 19 times
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639b1cb
Most Recent 4 months, 3 weeks ago
Selected Answer: B
Correct Answer: 2. No To meet the goal, you should use a tumbling window with a window size of 10 seconds, which would guarantee that each tweet is counted exactly once within each 10-second period.
upvoted 1 times
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AzureSQLDatabase
5 months ago
Selected Answer: A
This hopping is just gonna work like a regular tumbling. https://learn.microsoft.com/en-us/stream-analytics-query/hopping-window-azure-stream-analytics
upvoted 1 times
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Danweo
9 months, 3 weeks ago
Selected Answer: A
Overlapping only applies if the window size is larger than the hop size. Hopping is the same as tumbling with an equal hop to window size.
upvoted 1 times
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ageorgieva
10 months, 2 weeks ago
Selected Answer: B
The answer is B:No. Tumbling window should be used. With hopping window there is an overlap and an event can be counted more than once.
upvoted 1 times
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Dusica
1 year ago
Yes is correct
upvoted 1 times
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Alongi
1 year ago
Selected Answer: A
A. Yes A tumbling window is the same as an hopping window with the window size equal to the hop size.
upvoted 1 times
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Elanche
1 year, 1 month ago
B. No Using a hopping window with a hop size of 10 seconds and a window size of 10 seconds wouldn't ensure that each tweet is counted only once. A hopping window with these parameters would result in overlapping windows, which means that a tweet might fall into multiple windows and could potentially be counted multiple times. To ensure that each tweet is counted only once within a specific 10-second window, you should use a tumbling window with a size of 10 seconds. Tumbling windows are non-overlapping and fixed-size, ensuring that each tweet is counted within a single, distinct window.
upvoted 2 times
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moneytime
1 year, 2 months ago
Answer is Yes. The solution actually defined Tumbling window using hopping window. The condition is ; if the hopping size equals window size,then the window is also Tumbling.
upvoted 1 times
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Azure_2023
1 year, 2 months ago
Selected Answer: A
To make a Hopping window the same as a Tumbling window, specify the hop size to be the same as the window size.
upvoted 2 times
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sdg2844
1 year, 3 months ago
Selected Answer: A
While a tumbling window would be more straightforward, a Hopping window with 10/10 parameters will produce the same result, as it is set not to overlap.
upvoted 2 times
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sr0017
1 year, 3 months ago
risposta B corretta
upvoted 1 times
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Amir_Abed
1 year, 4 months ago
Answer should be B
upvoted 1 times
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6d954df
1 year, 4 months ago
A. Yes The proposed solution meets the goal. In Azure Stream Analytics, a hopping window generates output every hop size interval, and it aggregates events for the window size period. If both the hop size and window size are set to 10 seconds, the system will count the tweets in each 10-second window, ensuring each tweet is counted only once. This is because the window “hops” forward by the specified hop size (10 seconds in this case) and does not overlap with the next window. Therefore, each tweet will fall into exactly one window and will be counted once. This makes the hopping window suitable for this scenario.
upvoted 1 times
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positivitypeople
1 year, 4 months ago
Got this question today on the exam
upvoted 2 times
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Momoanwar
1 year, 4 months ago
Selected Answer: B
Chatgpt : No The answer is **B. No**, this does not meet the goal. Using a hopping window with both the hop size and the window size set to 10 seconds would result in each tweet being counted multiple times as each tweet could appear in several windows. To ensure each tweet is counted only once, the hop size should be equal to the window size or a different type of windowing, such as tumbling windows, should be used.
upvoted 2 times
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Community vote distribution
A (35%)
C (25%)
B (20%)
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