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From Artem Bogachev <artem.bogac...@ostrovok.ru>
Subject "Last One" Window
Date Thu, 19 May 2016 14:00:48 GMT

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

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
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?

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