The windowing capabilities of spark streaming determine the events in the RDD created for that time window. If the duration is 1s then all the events received in a particular 1s window will be a part of the RDD created for that window for that stream.
On Friday, July 4, 2014 1:28 PM, alessandro finamore <alessandro.finam...@polito.it> wrote: Thanks for the replies What is not completely clear to me is how time is managed. I can create a DStream from file. But if I set the window property that will be bounded to the application time, right? If I got it right, with a receiver I can control the way DStream are created. But, how can apply then the windowing already shipped with the framework if this is bounded to the "application time"? I would like to do define a window of N files but the window() function requires a duration as input... -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/window-analysis-with-Spark-and-Spark-streaming-tp8806p8824.html Sent from the Apache Spark User List mailing list archive at Nabble.com.
