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https://issues.apache.org/jira/browse/SPARK-5981?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Joseph K. Bradley updated SPARK-5981:
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Summary: pyspark ML models should support predict/transform on vector
within map (was: pyspark ML models fail during predict/transform on vector
within map)
> pyspark ML models should support predict/transform on vector within map
> -----------------------------------------------------------------------
>
> Key: SPARK-5981
> URL: https://issues.apache.org/jira/browse/SPARK-5981
> Project: Spark
> Issue Type: Improvement
> 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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