Hi, I am using the following code to generate the (score, count) for each window:
val score_count_by_window = topic.map(r => r._2) // r._2 is the integer score .countByValue() score_count_by_window.print() E.g. output for a window is as follows, which means that within the Dstream for that window, there are 2 rdds with score 0; 3 with score 1, and 1 with score -1. (0, 2) (1, 3) (-1, 1) I would like to get the aggregate count for each score over all windows until program terminates. I tried countByValueAndWindow() but the result is same as countByValue() (i.e. it is producing only per window counts). reduceByWindow also does not produce the result I am expecting. What is the correct way to sum up the counts over multiple windows? thanks -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Streaming-getting-total-count-over-all-windows-tp18888.html Sent from the Apache Spark User List mailing list archive at Nabble.com. --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org