Practice Test 2 | Google Cloud Certified Professional Data Engineer | Dumps | Mock Test

Answer: B.

A sliding time window uses time intervals in the data stream to define bundles of data. However, with sliding time windowing, the windows overlap. Each window might capture five minutes worth of data, but a new window starts every ten seconds. The frequency with which sliding windows begin is called the period. Therefore, our example would have a window size of five minutes and a period of ten seconds.

In this scenario, we want to get the average temperature per region by aggregating all events coming from sensors of that region. Sensor ID can be the key row. Sliding-time window aggregates event data in time window of 5 minutes, with sliding window of 60 seconds.

Source(s):

Windowing Functions: https://cloud.google.com/dataflow/model/windowing#windowing-functions

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Note: 

• 5 minutes is just an assumption to explain windowing through an example, where, for a time interval of compute a running average of the past five minutes’ worth of data is updated every ten seconds.
• Sliding window function produce an output only when an event occurs. Every window will have at least one event and the window continuously moves forward. In fixed window, it doesn’t have overlap and an event cannot belong to more than one fixed window. Each segment represents a distinct time segment.

1. The source of data is in different region and their data ingestion would not be same.
2. In sliding time Windows, the Window overlaps and window may be more that 1 Window..
3. In fixed Time Window, is good where streaming of data has limited source,

I think if you understand the windowing concept well and each of the 4 windowing functions, then sliding time window will appear as straight forward choice.

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