Hi Have you tested the Cloudera project: https://github.com/cloudera/spark-timeseries ? Let me know how did you progress on that route as I am also interested in that topic ?
Cheers On 26 June 2015 at 14:07, Caio Cesar Trucolo <truc...@gmail.com> wrote: > Hi everyone! > > I am working with multiple time series data and in summary I have to > adjust each time series (like inserting average values in data gaps) and > then training regression models with mllib for each time series. The > adjustment step I did with the adjustement function being mapped for each > element of RDD (in this case being the ID[as key] and the grouped by key > features). But for the regression models, it was not possible because the > functions need RDDs and my solution would be map each element (grouped as > time series) to a function of training. How can I deal with time series > data in this context with Spark? I did'nt find a way. > > Thank you > > -- > Caio > -- PGP KeyID: 2048R/EA31CFC9 subkeys.pgp.net
