Hi Mars, I guess my choice of words could have been better here! No problem with the buildpack, ran exactly as per instructions given.
I have the persistent fs setup but I'll look into it further, seems to fail on the very last step : ( Thanks for your input. Pat - sounds good, look forward to the announcement! On Tue, 10 Jan 2017 at 21:03 Mars Hall <[email protected]> wrote: > Hi Daniel, > > If you think there's a problem with the PredictionIO buildpack for Heroku, > please file as issue on its GitHub repo > https://github.com/heroku/predictionio-buildpack/issues > > If it works locally but not on Heroku, my wild guess is that one of your > algorithms is serializing the model to the filesystem, and it's throwing an > error when trying to retrieve that model. Heroku does not support > filesystem persistence between runs (e.g. files committed during > release/train will not persist to web/deploy) > > Perhaps try enabling S3 HDFS for filesystem persistence > https://github.com/heroku/predictionio-buildpack/blob/master/CUSTOM.md#optional-persistent-filesystem > Note that with HDFS filesystem path references must be from `/` root, not > nested in a User ID directory. > > *Mars > > ( <> .. <> ) > > > On Jan 10, 2017, at 00:53, Daniel O' Shaughnessy < > [email protected]> wrote: > > > > Hi Pat, > > > > Ya I guess it's an issue with the pio heroku buildpack. It seems to > build and train OK based on the logs but then throws that error when trying > to deploy. > > > > I'm not actually using the similar products template I'm using this: > https://github.com/apache/incubator-predictionio-template-ecom-recommender > > > > I'm trying to extend the ecom template to include 'likes' to try and > improve the results and using the tutorial as a guideline. I'm using this > for an app store recommender...Ideally I'd be using the UR but I can't get > this up on Heroku so far, when AWS approve it I may go down that route for > hosting eventually. > > > > On Mon, 9 Jan 2017 at 20:44 Pat Ferrel <[email protected]> wrote: > > AFAIK, the Heroku support is fairly new so not surprising that a > multiple engine template has trouble. Multiple Algorithms in a Template are > fairly rare. I’d ask Heroku what is going on. > > > > BTW what are you using this for? There are other ways to get similar > products—some of which may work better. For instance is there a reason for > multiple algorithms? > > > > > > > > On Jan 9, 2017, at 10:45 AM, Daniel O' Shaughnessy < > [email protected]> wrote: > > > > Hi, > > > > I'm attempting to add a like/dislike event to the ecom recommender ( as > per > http://predictionio.incubator.apache.org/templates/similarproduct/multi-events-multi-algos/ > ). This method combines the results of 2 separate algorithms in the Serving > class. > > > > When I deploy this using the predictionIO Heroku buildpack it seems to > deploy and run the release command OK but when I check the Heroku logs it > fails here: > > > > 2017-01-09T15:32:44.905195+00:00 app[web.1]: [INFO] [Engine] Using > persisted model > > > > 2017-01-09T15:32:44.912783+00:00 app[web.1]: [INFO] [Engine] Loaded > model com.dos.sfdc.ECommModel for algorithm com.dos.sfdc.ECommAlgorithm > > > > 2017-01-09T15:32:45.307111+00:00 app[web.1]: [INFO] [Engine] > Custom-persisted model detected for algorithm com.dos.sfdc.LikeAlgorithm > > > > 2017-01-09T15:32:45.668678+00:00 app[web.1]: [ERROR] [OneForOneStrategy] > Cannot call methods on a stopped SparkContext. > > > > 2017-01-09T15:32:45.668690+00:00 app[web.1]: This stopped SparkContext > was created at: > > > > 2017-01-09T15:32:45.668691+00:00 app[web.1]: > > > > 2017-01-09T15:32:45.668692+00:00 app[web.1]: > org.apache.spark.SparkContext.<init>(SparkContext.scala:82) > > > > 2017-01-09T15:32:45.668693+00:00 app[web.1]: > org.apache.predictionio.workflow.WorkflowContext$.apply(WorkflowContext.scala:45) > > > > 2017-01-09T15:32:45.668694+00:00 app[web.1]: > org.apache.predictionio.workflow.CreateServer$.createServerActorWithEngine(CreateServer.scala:228) > > > > Anyone come across this before? > > > > > > > > Thanks, > > > > > > > > Daniel. > > > > > >
