+1, having the convenient creation of pipelines for Java is more of a long term project, but we should make it possible to manually create pipelines in Java.
On Fri, Sep 18, 2015 at 11:15 AM, Till Rohrmann <till.rohrm...@gmail.com> wrote: > Hi Alexey and Hanan, > > one of FlinkML’s feature is the flexible pipelining mechanism. It allows > you to chain multiple transformers with a trailing predictor to form a data > analysis pipeline. In order to support multiple input types, the actual > program logic (matching for the type) is assembled at compile time by the > Scala compiler using implicits. That is also the reason why you see in Java > the fourth parameter fitOperation when calling > multipleLinearRegression.fit() which in Scala is an implicit parameter. In > theory, it is possible to construct the pipelines yourself in Java by > assembling explicitly the respective implicit operations. However, I would > refrain from doing so, because it is error prone and laborious. > > At the moment, I don’t really see an easy solution how to port the > pipelining mechanism to Java (8), because of the missing feature of > implicits. However, what we could do is to provide fit, predict and > transform method which can be used without the chaining support. Then you > lose the pipelining, but you can do it manually by calling the methods > (e.g. fit and transform) for each stage. We could add a thin Java layer > which calls the Scala methods with the correctly instantiated operations. > > Cheers, > Till > > > On Thu, Sep 17, 2015 at 7:05 PM, Alexey Sapozhnikov <ale...@scalabill.it> > wrote: > > > Hello everyone. > > > > Do you have a sample in Java how to implement Flink > > MultipleLinearRegression example? > > Scala is great, however we would like to see the exact example we could > > invoke it from Java if it is possible. > > Thanks and sorry for the interrupt. > > > > > > > > On Thu, Sep 17, 2015 at 4:27 PM, Hanan Meyer <ha...@scalabill.it> wrote: > > > > > Hi > > > > > > I'm using Flink ML 9.2.1 in order to perform a multiple linear > regression > > > with a csv data file. > > > > > > The Scala sample code for it is pretty straightforward: > > > val mlr = MultipleLinearRegression() > > > > > > val parameters = ParameterMap() > > > > > > parameters.add(MultipleLinearRegression.Stepsize, 2.0) > > > parameters.add(MultipleLinearRegression.Iterations, 10) > > > parameters.add(MultipleLinearRegression.ConvergenceThreshold, 0.001) > > > val inputDS = env.fromCollection(data) > > > > > > mlr.fit(inputDS, parameters) > > > > > > When I'm using Java(8) the fit method includes 3 parameters > > > 1. dataset > > > 2.parameters > > > 3. object which implements -fitOperation interface > > > > > > multipleLinearRegression.fit(regressionDS, parameters,fitOperation); > > > > > > Is there a need to implement the fitOperation interface which have > been > > > already > > > implemented in Flinks ml source code. > > > > > > Another option is using MultipleLinearRegression.fitMLR() method ,but I > > > haven't found a way to pass the train dataset to it as a parameter or > by > > > setter. > > > > > > I'll be more than happy if you could guide me how to implement it in > Java > > > > > > Thanks > > > > > > Hanan Meyer > > > > > > > > > > > > > > > > > > > > > -- > > > > *Regards* > > > > *Alexey Sapozhnikov* > > CTO& Co-Founder > > Scalabillit Inc > > Aba Even 10-C, Herzelia, Israel > > M : +972-52-2363823 > > E : ale...@scalabill.it > > W : http://www.scalabill.it > > YT - https://youtu.be/9Rj309PTOFA > > Map:http://mapta.gs/Scalabillit > > Revolutionizing Proof-of-Concept > > >
