Azure Stream Analytics

Question 1

Sliding window function

Answer 1

Output produced only when an event occurs. Events can belong to more than one window.

Question 2

Session windowing function

Answer 2

The session windowing function allows you to group streaming events that arrive at similar time, and filter out time periods where no data exists. It’s native to Stream Analytics

Question 3

Tumbling windowing function

Answer 3

Segment data into distinct time segments. They repeat, do not overlap and an event can’t belong to more than one window.

Question 4

Hopping windowing function

Answer 4

Hopping window functions hop forward in time by a fixed period. They can overlap, to make them the same as the tumbling window specify the same hop size and window size.