How to forecast problem in spark arima?

[jinxiu2216]

Hi，
I have got TimeSeriesRDD in spark, but I don't know how to get the forecast.

val rdd = sc.textFile(path).map { line =>
val tokens = line.split(",")
val series = new DenseVector(tokens.tail.map(_.toDouble))
(tokens.head, series.asInstanceOf[Vector])
}

val start = ZonedDateTime.of(2015, 4, 9, 0, 0, 0, 0, ZoneId.of("Z"))
val index = uniform(start, 250, new DayFrequency(1))
val tsRDD = new TimeSeriesRDD(index, rdd);
val arimaModel = tsRDD.map(tuple => (tuple._1, ARIMA.fitModel(1,0,1,tuple._2)))

Thanks

[debasish83]

Forecast API we can add it...idea is that we use one-step ahead prediction and then add the predicted point back to the time-series to predict the next step...as the prediction horizon increases error will be impacted...are you looking into specific problem ?? The current ARIMA model can be used with a ringbuffer support...