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https://issues.apache.org/jira/browse/SPARK-19683?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15876812#comment-15876812
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Sean Owen commented on SPARK-19683:
-----------------------------------
This is trivial for an application to implement. Unless it is a common format
extension and one the core library can use, is there much particular reason for
it to be in Spark vs app or external lib?
> Support for libsvm-based learning-to-rank format
> ------------------------------------------------
>
> Key: SPARK-19683
> URL: https://issues.apache.org/jira/browse/SPARK-19683
> Project: Spark
> Issue Type: New Feature
> Components: ML, MLlib
> Affects Versions: 2.1.0
> Reporter: Craig Macdonald
> Priority: Minor
>
> I would like to use Spark for reading/processing Learning to Rank files. The
> standard format is an extension of libsvm:
> {code}
> 0 qid:1 1:2.9 2:9.4 # docid=clueweb09-00-01492
> {code}
> Under the mlib API, a LabeledPoint would need an extension called
> QueryLabeledPoint.
> I would also like to investigate use through the DataFrame, extending the
> libsvm source, however many of the classes/methods used there are private
> (e.g. LibSVMOptions, Datatype.sameType(), VectorUDT). So would an extension
> to handle LTR format be better inside Spark or outside?
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