You can also serialize the model and use it in other places. Best Regards, Sonal Founder, Nube Technologies <http://www.nubetech.co>
<http://in.linkedin.com/in/sonalgoyal> On Wed, Dec 10, 2014 at 5:32 PM, Yanbo Liang <yanboha...@gmail.com> wrote: > Hi Klaus, > > There is no ideal method but some workaround. > Train model in Spark cluster or YARN cluster, then use RDD.saveAsTextFile > to store this model which include weights and intercept to HDFS. > Load weights file and intercept file from HDFS, construct a GLM model, and > then run model.predict() method, you can get what you want. > > The Spark community also have some ongoing work about export model with > PMML. > > 2014-12-10 18:32 GMT+08:00 Simon Chan <simonc...@gmail.com>: > >> Hi Klaus, >> >> PredictionIO is an open source product based on Spark MLlib for exactly >> this purpose. >> This is the tutorial for classification in particular: >> http://docs.prediction.io/classification/quickstart/ >> >> You can add custom serving logics and retrieve prediction result through >> REST API/SDKs at other places. >> >> Simon >> >> >> On Wed, Dec 10, 2014 at 2:25 AM, Klausen Schaefersinho < >> klaus.schaef...@gmail.com> wrote: >> >>> Hi, >>> >>> >>> I would like to use Spark to train a model, but use the model in some >>> other place,, e.g. a servelt to do some classification in real time. >>> >>> What is the best way to do this? Can I just copy I model file or >>> something and load it in the servelt? Can anybody point me to a good >>> tutorial? >>> >>> >>> Cheers, >>> >>> >>> Klaus >>> >>> >>> >>> -- >>> “Overfitting” is not about an excessive amount of physical exercise... >>> >> >> >
