Hello guys..i know its irrelevant to this topic but i've been looking desperately for the solution. I am facing en exception http://apache-spark-user-list.1001560.n3.nabble.com/how-to-resolve-you-must-build-spark-with-hive-exception-td27390.html
plz help me.. I couldn't find any solution.. plz On Fri, Jul 22, 2016 at 6:12 PM, Sean Owen <so...@cloudera.com> wrote: > No there isn't anything in particular, beyond the various bits of > serialization support that write out something to put in your storage > to begin with. What you do with it after reading and before writing is > up to your app, on purpose. > > If you mean you're producing data outside the model that your model > uses, your model data might be produced by an RDD operation, and saved > that way. There it's no different than anything else you do with RDDs. > > What part are you looking to automate beyond those things? that's most of > it. > > On Fri, Jul 22, 2016 at 2:04 PM, Sergio Fernández <wik...@apache.org> > wrote: > > Hi Sean, > > > > On Fri, Jul 22, 2016 at 12:52 PM, Sean Owen <so...@cloudera.com> wrote: > >> > >> If you mean, how do you distribute a new model in your application, > >> then there's no magic to it. Just reference the new model in the > >> functions you're executing in your driver. > >> > >> If you implemented some other manual way of deploying model info, just > >> do that again. There's no special thing to know. > > > > > > Well, because some huge model, we typically bundle both logic > > (pipeline/application) and models separately. Normally we use a shared > > stores (e.g., HDFS) or coordinated distribution of the models. But I > wanted > > to know if there is any infrastructure in Spark that specifically > addresses > > such need. > > > > Thanks. > > > > Cheers, > > > > P.S.: sorry Jacek, with "ml" I meant "Machine Learning". I thought is a > > quite spread acronym. Sorry for the possible confusion. > > > > > > -- > > Sergio Fernández > > Partner Technology Manager > > Redlink GmbH > > m: +43 6602747925 > > e: sergio.fernan...@redlink.co > > w: http://redlink.co > > --------------------------------------------------------------------- > To unsubscribe e-mail: user-unsubscr...@spark.apache.org > >
