In Structured Streaming, there's the notion of event-time windowing:
However, this is not quite similar to DStream's windowing operations: in Structured Streaming, windowing groups the data by fixed time-windows, and every event in a time window is associated to its group: And in DStreams it just outputs all the data according to a limited window in time (last 10 minutes for example). The question was asked also here <https://stackoverflow.com/questions/49821646/is-there-someway-to-do-the-eqivalent-of-reducebykeyandwindow-in-spark-structured> , if it makes it clearer. How the latter can be achieved in Structured Streaming? -- Sent from: http://apache-spark-user-list.1001560.n3.nabble.com/ --------------------------------------------------------------------- To unsubscribe e-mail: user-unsubscr...@spark.apache.org
