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https://issues.apache.org/jira/browse/SYSTEMML-995?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15539269#comment-15539269
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Matthias Boehm commented on SYSTEMML-995:
-----------------------------------------
yes, that's true we should do the same as for matrices here - thanks for taking
it over.
Apart, from that there are some smaller remaining issues: (1) input handling
with read statements (inputs not found), and (2) column name schema
pass-through, which is primarily needed for transform as users are free to
provide a transform specification based on column names instead of column
indexes.
> MLContext dataframe-frame conversion with index column & vector column
> ----------------------------------------------------------------------
>
> Key: SYSTEMML-995
> URL: https://issues.apache.org/jira/browse/SYSTEMML-995
> Project: SystemML
> Issue Type: Bug
> Components: APIs
> Affects Versions: SystemML 0.11
> Reporter: Matthias Boehm
> Priority: Blocker
>
> MLContext currently always assumes data frame to frame conversion without
> existing index column. Since the user cannot communicate the existence of
> this column, the data conversion leads to incorrect results as an additional
> column is included in the output frame. We need make the MLContext handling
> of frames consistent with the handling of matrices.
> Additionally, the conversion code in
> {{MLContextConversionUtil.dataFrameToFrameObject()}} does not yet take into
> account frames with vectors, although the recent addition adds this support
> in the underlying {{FrameRDDConverterUtils.java}} class. Therefore, the
> number of columns set when {{mc == null}} is incorrect.
> Thanks [~mwdus...@us.ibm.com] for catching this issue. cc [~acs_s] [~deron]
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