Which Windowing Features Detect Changed Content in Stream Analytics Jobs? | Exam DP-203 | Microsoft

Correct Answer: C

It is the sliding window that outputs the events only when the content of the window really changed in Stream Analytics jobs.Option A is incorrect.

A Tumbling window function segments a data stream into a contiguous series of fixed size, non-overlapping time segments and works against them.

Option B is incorrect.

There is no windowing function like Topping Window.

Option C is correct.

The sliding window function is used to output the events only when the content of the window really changed in Stream Analytics jobs.

Option D is incorrect.

Session window function groups events arriving at similar times, filtering out points/periods of time where there exists no data.

Option E is incorrect.

The snapshot window function is used to group the events having the same timestamp.

To know more about Windowing functions, please visit the below-given link:

The correct answer is E. Snapshot Window.

Windowing is a feature in Stream Analytics that allows you to divide a data stream into distinct sets of data for processing. These sets, or windows, can be based on time or count, and they can overlap or be non-overlapping. The different types of windows are used to support various processing scenarios.

A Tumbling Window is a non-overlapping window that is fixed in size and moves continuously over the data stream. For example, if you have a tumbling window of 5 minutes, the window would move over the data stream every 5 minutes and include only the events that occurred during that 5-minute interval.

A Topping Window is similar to a tumbling window, but it includes a fixed number of the most recent events, rather than a fixed time interval.

A Sliding Window is an overlapping window that moves over the data stream in a continuous manner, similar to a tumbling window. However, sliding windows overlap with each other and include events from multiple windows. For example, if you have a sliding window of 5 minutes and a slide interval of 1 minute, the window would move every minute and include events from the previous 5 minutes.

A Session Window is a window that groups events together based on a gap of inactivity between them. If there is no activity for a certain period of time, the window is closed and the events are processed. This is useful for scenarios where you want to group together events that are related in some way, but may not occur at fixed intervals.

A Snapshot Window is a special type of window that only outputs events when the content of the window really changes. This means that if there are no new events or changes to the existing events in the window, no output is produced. This is useful for scenarios where you want to reduce the amount of duplicate data being processed, or when you only want to process data when it is truly relevant.

Therefore, to output the events only when the content of the window really changes in Stream Analytics jobs, you would use the Snapshot Window feature.