Some extra work is needed to close the loop. One related example is streaming linear regression added by Jeremy very recently:
https://github.com/apache/spark/blob/master/examples/src/main/scala/org/apache/spark/examples/mllib/StreamingLinearRegression.scala You can use a model trained offline to serve a DStream and save the predictions (also a DStream) to somewhere, e.g., HDFS or stdout. Best, Xiangrui On Mon, Aug 4, 2014 at 9:28 PM, Hoai-Thu Vuong <thuv...@gmail.com> wrote: > Hello everybody! > > I'm getting started with spark and mllib. I'm successful in building a small > cluster and follow the tutorial. However, I would like to ask about how to > use the model, which is trained by mllib. I understand that, with data we > can training the model such as Classifier model, then use it to classify new > input. Is there any case study to build a service upon spark or hdfs and > using model (trained by above steps) and give output to user (class of input > data). Thank you very much! > > > > -- > Thu. --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org
