Data Platform Tips 71 - Windowing functions in Azure Stream Analytics

Windowing function must be used in Azure Stream Analytics when using aggregate functions and GROUP BY clause. Stream Analytics provides four windowing functions. They are

• Sliding Window
• Tumbling Window
• Hopping Window
• Session Window

Sliding windows consider all possible windows of the given length. To make the number of windows manageable for Stream Analytics, sliding windows produce an output only when an event enters or exits the window. Every window has at least one event, and each event can be in more than one sliding window. Sliding windows overlap.



Tumbling windows are fixed-size windows that do not overlap and are contiguous. When the timespan of the window size has passed, a new window is immediately created with the same duration.









Hopping windows are used to specify overlapping windows that are scheduled. Hopping windows are defined with a windowsize, hopsize, and timeunit.






Session window functions group events that arrive at similar times, filtering out periods of time where there is no data.