Which windowing function should you use to perform the streaming aggregation of the sales data?

Which windowing function should you use to perform the streaming aggregation of the sales data?
A . Sliding
B. Hopping
C. Session
D. Tumbling

View Answer

Answer: D

Explanation:

Scenario: The sales data, including the documents in JSON format, must be gathered as it arrives and analyzed online by using Azure Stream Analytics. The analytics process will perform aggregations that must be done continuously, without gaps, and without overlapping.

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.

Timeline

Description automatically generated

Reference: https://github.com/MicrosoftDocs/azure-docs/blob/master/articles/stream-analytics/stream-analytics-window-functions.md