[jira] [Commented] (SPARK-14707) Linear algebra: clarify light vs heavy constructors and accesors

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

    [ https://issues.apache.org/jira/browse/SPARK-14707?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15246192#comment-15246192 ] 

Joseph K. Bradley commented on SPARK-14707:
-------------------------------------------

We'll need to wait until the linear algebra refactoring is complete: [SPARK-13944]

> Linear algebra: clarify light vs heavy constructors and accesors
> ----------------------------------------------------------------
>
>                 Key: SPARK-14707
>                 URL: https://issues.apache.org/jira/browse/SPARK-14707
>             Project: Spark
>          Issue Type: Improvement
>          Components: ML
>            Reporter: Joseph K. Bradley
>
> MLlib linear algebra provides methods for constructing Vectors and Matrices and for accessing the vector/matrix data.  There are currently 2 types of these constructors and accessors:
> * light: avoid data copy and validation, useful for converting between MLlib types and numpy, Breeze, etc.
> * heavy: copy or validate data, useful for constructing MLlib types from user inputs
> MLlib is not very consistent about these and does not document which ops are light vs. heavy.  This JIRA is for:
> * First, discussing which ops should be light vs heavy to choose a consistent API
> * Next, creating subtasks for Scala and Python for updating the implementations and clarifying the docs



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