Hi all, I am trying to figure out how to perform equivalent of "Session windows" (as mentioned in https://cloud.google.com/dataflow/model/windowing) using spark streaming. Is it even possible (i.e. possible to do efficiently at scale). Just to expand on the definition:
Taken from the google dataflow documentation: The simplest kind of session windowing specifies a minimum gap duration. All data arriving below a minimum threshold of time delay is grouped into the same window. If data arrives after the minimum specified gap duration time, this initiates the start of a new window. Any help would be appreciated. -- Ankur Chauhan
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