[jira] [Updated] (SPARK-5981) pyspark ML models fail during predict/transform on vector within map

["Joseph K. Bradley (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-5981?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Joseph K. Bradley updated SPARK-5981:
-------------------------------------
    Priority: Major  (was: Critical)

> pyspark ML models fail during predict/transform on vector within map
> --------------------------------------------------------------------
>
>                 Key: SPARK-5981
>                 URL: https://issues.apache.org/jira/browse/SPARK-5981
>             Project: Spark
>          Issue Type: Bug
>          Components: MLlib, PySpark
>    Affects Versions: 1.3.0
>            Reporter: Joseph K. Bradley
>
> Many Python ML models and transformers use JavaModelWrapper to call methods in the JVM, such as predict() and transform().  It is common to write:
> {code}
> data.map(lambda features: model.predict(features))
> {code}
> This fails because JavaModelWrapper.call uses the SparkContext (within the transformation).
> Note: It is possible to do a workaround using batch predict if models/transformers support it:
> {code}
> model.predict(data)
> {code}
> However, this is still a major problem.



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