Hi, I am working with time series data in the form of (timestamp, name, value), and an event time that is the timestamp when the data was published onto kafka, and I have a business requirement in which each stream element becomes enriched, and then processing requires different time series names to be processed in different windows with different time averages.
For example, time series with name "a" might require a one minute window, and five minute window. time series with name "b" requires no windowing. time series with name "c" requires a two minute window and 10 minute window. Does flink support this style of windowing? I think it doesn't. Also, does any streaming platform support that type of windowing? I was thinking that this type of windowing support might require a different flink deployment per each window. Would that scale though, if there are tens of thousands of time series names / windows? Any help or advice would be appreciated. Thank you. Marco A. Villalobos
