Hi, I would first compute the 15 minute counts. Based on these counts, you compute the threshold by computing average and std-dev and then you compare the counts with the threshold. In pseudo code this could look as follows:
DataStream requests = ... DataStream counts = requests.timeWindow(15 mins).reduce(// count requests) DataStream thresholds = counts.timeWindow(15 mins, 6 hours).apply(// compute every 15 mins average and std-dev over 6 hours) DataStream alerts = counts.connect(thresholds).process(// stateful CoProcessFunction that compares thresholds with counts) Hope this helps, Fabian 2017-07-28 18:31 GMT+02:00 Raj Kumar <smallthings1...@gmail.com>: > Hi, > > I am using a sliding window to monitor server performance. I need to keep > track of number of HTTP requests generated and alert the user when the > requests gets too high(Sliding window of 6 hours which slides every > 15mins). > Aggregate count of the number of http requests is evaluated in the 15mins > sliding window. I need to keep track of running average of these aggregate > count over the different sliding window of 15mins to create an alert when > the load is over the average+1std deviation. > > How can we achieve this ? How can we keep track of running average for the > all the sliding windows ? > P > > > > -- > View this message in context: http://apache-flink-user- > mailing-list-archive.2336050.n4.nabble.com/Access-Sliding- > window-tp14519.html > Sent from the Apache Flink User Mailing List archive. mailing list archive > at Nabble.com. >
