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Posted to issues@spark.apache.org by "Hyukjin Kwon (JIRA)" <ji...@apache.org> on 2019/05/21 04:34:32 UTC
[jira] [Resolved] (SPARK-14707) Linear algebra: clarify light vs
heavy constructors and accessors
[ https://issues.apache.org/jira/browse/SPARK-14707?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Hyukjin Kwon resolved SPARK-14707.
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Resolution: Incomplete
> Linear algebra: clarify light vs heavy constructors and accessors
> -----------------------------------------------------------------
>
> Key: SPARK-14707
> URL: https://issues.apache.org/jira/browse/SPARK-14707
> Project: Spark
> Issue Type: Improvement
> Components: ML
> Reporter: Joseph K. Bradley
> Priority: Major
> Labels: bulk-closed
>
> 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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