[jira] [Assigned] (PIO-138) Batch predict fails when using a PersistentModel

["Mars Hall (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/PIO-138?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Mars Hall reassigned PIO-138:
-----------------------------

    Assignee: Mars Hall

> Batch predict fails when using a PersistentModel
> ------------------------------------------------
>
>                 Key: PIO-138
>                 URL: https://issues.apache.org/jira/browse/PIO-138
>             Project: PredictionIO
>          Issue Type: Bug
>          Components: Core
>    Affects Versions: 0.12.0-incubating
>            Reporter: Mars Hall
>            Assignee: Mars Hall
>
> Issue based on a PR/issue opened on GitHub:
> https://github.com/apache/incubator-predictionio/pull/441
> h2. Problem
> {quote}pio batchpredict --input /tmp/pio/batchpredict-input.json --output /tmp/pio/batchpredict-output.json
> [WARN] [ALSModel] Product factor is not cached. Prediction could be slow.
> Exception in thread "main" org.apache.spark.SparkException: Only one SparkContext may be running in this JVM (see SPARK-2243). To ignore this error, set spark.driver.allowMultipleContexts = true. {quote}
> h2. Root Cause
> BatchPredict makes multiple SparkContexts:
> https://github.com/apache/incubator-predictionio/blob/v0.12.0-incubating/core/src/main/scala/org/apache/predictionio/workflow/BatchPredict.scala#L160
> https://github.com/apache/incubator-predictionio/blob/v0.12.0-incubating/core/src/main/scala/org/apache/predictionio/workflow/BatchPredict.scala#L183
> When using a {{PersistentModel}}/{{PersistentModelLoader}}, PredictionIO don't stop the first SparkContext:
> https://github.com/apache/incubator-predictionio/blob/v0.12.0-incubating/core/src/main/scala/org/apache/predictionio/controller/Engine.scala#L241-L250
> For example, the Recommendation Engine Template uses this technique:
> https://github.com/apache/incubator-predictionio-template-recommender/blob/develop/src/main/scala/ALSModel.scala
> h2. Solutions?
> Due to the variability of SparkContext usage during deploy, how do we ensure a viable SparkContext for running batch queries? 



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