Thank you for your suggestion, Stefano. I was hoping for an easier solution :)

Sent from my iPhone

> On Oct 30, 2015, at 2:11 PM, Stefano Baghino <stefano.bagh...@radicalbit.io> 
> wrote:
> 
> One possibility would be to export the model as a PMML (Predictive Model 
> Markup Language, an XML-based standard to describe predictive models) and 
> then use it in your Web app (using something like JPMML, for example). You 
> can directly export (some) models (including LinReg) since Spark 1.4: 
> https://databricks.com/blog/2015/07/02/pmml-support-in-spark-mllib.html
> 
> For more info on PMML support on MLlib (including model support): 
> https://spark.apache.org/docs/latest/mllib-pmml-model-export.html
> For more info on the PMML standard: 
> http://dmg.org/pmml/v4-2-1/GeneralStructure.html
> 
>> On Fri, Oct 30, 2015 at 9:33 PM, vijuks <vij...@gmail.com> wrote:
>> I want to load a model saved by a spark machine learning job, in a web
>> application.
>> 
>>                         model.save(jsc.sc(), "myModelPath");
>> 
>>                         LogisticRegressionModel model = 
>> LogisticRegressionModel.load(
>>                                         jsc.sc(), "myModelPath");
>> 
>> When I do that, I need to pass a spark context for loading the model.  The
>> model is small and can be saved to local file system, so is there any way to
>> use it with out the spark context?  Looks like creating spark context is an
>> expensive step that starts http server that listens on multiple ports.
>> 
>> 15/10/30 10:53:39 INFO HttpServer: Starting HTTP Server
>> 15/10/30 10:53:39 INFO Utils: Successfully started service 'HTTP file
>> server' on port 63341.
>> 15/10/30 10:53:39 INFO SparkEnv: Registering OutputCommitCoordinator
>> 15/10/30 10:53:40 INFO Utils: Successfully started service 'SparkUI' on port
>> 4040.
>> 15/10/30 10:53:40 INFO SparkUI: Started SparkUI at http://171.142.49.18:4040
>> 
>> 
>> 
>> 
>> 
>> 
>> 
>> 
>> --
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>> 
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> 
> 
> 
> -- 
> BR,
> Stefano Baghino
> 
> Software Engineer @ Radicalbit

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