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https://issues.apache.org/jira/browse/SPARK-16074?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15340642#comment-15340642
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Xiangrui Meng commented on SPARK-16074:
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Picked option 2) because we don't have any Java source code in MLlib. The
overhead for Java users is the extra `()`.
> Expose VectorUDT/MatrixUDT in a public API
> ------------------------------------------
>
> Key: SPARK-16074
> URL: https://issues.apache.org/jira/browse/SPARK-16074
> Project: Spark
> Issue Type: New Feature
> Components: MLilb
> Affects Versions: 2.0.0
> Reporter: Xiangrui Meng
> Assignee: Xiangrui Meng
> Priority: Critical
>
> Both VectorUDT and MatrixUDT are private APIs, because UserDefinedType itself
> is private in Spark. However, in order to let developers implement their own
> transformers and estimators, we should expose both types in a public API to
> simply the implementation of transformSchema, transform, etc. Otherwise, they
> need to get the data types using reflection.
> Note that this doesn't mean to expose VectorUDT/MatrixUDT classes. We can
> just have a method or a static value that returns VectorUDT/MatrixUDT
> instance with DataType as the return type. There are two ways to implement
> this:
> 1. following DataTypes.java in SQL, so Java users doesn't need the extra "()".
> 2. Define DataTypes in Scala.
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