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https://issues.apache.org/jira/browse/SPARK-17311?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Apache Spark reassigned SPARK-17311:
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Assignee: Apache Spark (was: Sean Owen)
> Standardize Python-Java MLlib API to accept optional long seeds in all cases
> ----------------------------------------------------------------------------
>
> Key: SPARK-17311
> URL: https://issues.apache.org/jira/browse/SPARK-17311
> Project: Spark
> Issue Type: Bug
> Components: MLlib, PySpark
> Affects Versions: 2.0.0
> Reporter: Sean Owen
> Assignee: Apache Spark
> Priority: Minor
>
> (Note this follows on https://issues.apache.org/jira/browse/SPARK-16832 )
> There are a few seed-related issues in the Pyspark-MLLib bridge:
> - {{PythonMLlibAPI}} methods that take a seed don't always take a
> {{java.lang.Long}} consistently, allowing the Python API to specify "no seed"
> - .mllib's {{Word2VecModel}} seems to be an odd man out in .mllib in that it
> picks its own random seed. Instead it should default to None, meaning,
> letting the Scala implementation pick a seed
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