Aljoscha answered this in the other thread you started for this
("'Last One' Window")On Fri, May 20, 2016 at 12:43 PM, Artem Bogachev <artem.bogac...@ostrovok.ru> wrote: > Hi, > > I’ve faced a problem trying to model our platform using Flink Streams. > > Let me describe our model: > > // Stream of data, ex. stocks: (AAPL, 100.0), (GZMP, 100.0) etc. > val realData: DataStream[(K, V)] = env.addSource(…) > > // Stream of forecasts (same format) based on some window aggregates > val forecastedData: DataStream[(K, V)] = > realData.keyBy(1).timeWindow(Time.minutes(FORECAST_INTERVAL)).apply(new > Forecaster(…)) > > I would like to construct a stream errors, which values are just differences > between realData stream and the latest available forecast for this key in > forecastedData stream > > // I suppose this solution does not guarantee that all realData values will > have corresponding forecast > val errors: DataStream[(K, V)] = > realData.join(forecastedData).where(0).equal(0)… > > Could you give an advice on how to implement such pattern? Do I have to > write custom windows? > > Artem
