Thanks Donald. I used this command but am still getting this error. It doesn't seem to be adjusting the configuration. Do you see a problem in how I used the spark-submit options. The train function ran but the error makes me think the sparkResultSize was not adjusted.
command: bin/pio build --verbose; bin/pio train -- --driver-memory 14G -- --conf spark.driver.max ResultSize=4g; bin/pio deploy error: Job aborted due to stage failure: Total size of serialized results of 8 tasks (1236.7 MB) is bigger than spark.driver.maxResultSize (1024.0 MB) Regarding the PAlgorithm, what I am trying to do is save a Map in the train method to reuse in the predict method. Because of the error above I am not able to convert my RDD to a map as the collectAsMap tries to bring it to the driver. If I use the PAlgorithm, I should be able to just save the RDD in the Model class and then use it in the predict method. I am going down that path now. *Do you know of any templates that are using the PAlgorithm?* The docs say that "Similar Product" uses it but it looks like it uses the P2LAlgorithm. Thank you for your help. *Shane Johnson | 801.360.3350* LinkedIn <https://www.linkedin.com/in/shanewjohnson> | Facebook <https://www.facebook.com/shane.johnson.71653> 2018-02-22 8:16 GMT-10:00 Donald Szeto <don...@apache.org>: > Hi Shane, > > I think what you are looking for to set max result size on the driver is > by passing in a spark-submit argument that looks something like this: > > pio train ... -- --conf spark.driver.maxResultSize=4g ... > > Regarding PAlgorithm, the predict() method does not actually have the > SparkContext in it (http://predictionio.apache. > org/api/current/#org.apache.predictionio.controller.PAlgorithm). The > "model" argument, unlike P2LAlgorithm, can contain RDDs. In > PAlgorithm.predict(), you would be able to perform RDD operations directly > on the model argument. If the SparkContext is needed, the context() method > can be used on the model RDD. > > Hope these help. > > Regards, > Donald > > On Wed, Feb 21, 2018 at 12:08 PM Shane Johnson < > shanewaldenjohn...@gmail.com> wrote: > >> Hi team, >> >> We have a specific use case where we are trying to save off a map from >> the train function and reuse it in the predict function to increase our >> predict function response time. I know the collect() forces everything to >> the driver. We are collecting the RDD to a map as we don't have a spark >> context in the predict function. >> >> I am getting this error and am looking for a way to adjust the parameter >> from 1G to 4G+. I can see a way to do it in Spark 1.6 but we are using >> Spark 2.1.1 and I have not seen the ability to set this. *Has anyone >> been able to adjust the maxResultSize to something more than 1G?* >> >> Exception in thread "main" org.apache.spark.SparkException: Job aborted due >> to stage failure: Total size of serialized results of 7 tasks (1156.3 MB) is >> bigger than spark.driver.maxResultSize (1024.0 MB) >> >> >> I have tried to set this parameter but get this as a result with Spark >> 2.1.1 >> >> Error: Unrecognized option: --driver-maxResultSize >> >> Our other option is to do the work to obtain a spark context in the >> predict function so we can pass the RDD through from the train to predict >> function. The documentation was a little unclear to me on PredictionIO. *Is >> this the right place to learn how to get a spark context in the predict >> function?* https://predictionio.incubator.apache.org/ >> templates/vanilla/dase/ >> >> Also I am not seeing in this documentation how to get the spark context >> into the predict function, it looks like it is only used in the train >> function. >> >> Thanks in advance for your expertise. >> >> *Shane Johnson | 801.360.3350 <(801)%20360-3350>* >> LinkedIn <https://www.linkedin.com/in/shanewjohnson> | Facebook >> <https://www.facebook.com/shane.johnson.71653> >> >