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https://issues.apache.org/jira/browse/ARROW-1983?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16853433#comment-16853433
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Wes McKinney commented on ARROW-1983:
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Yes. I don't think it necessarily to resolve all of this in a single patch, so
we can open a follow-up JIRA to implement the optimization to read a row group
given a _metadata file. There is some other complexity there such as how to
open the filepath (you need a FileSystem handle -- see the filesystem API work
that is in process)
> [Python] Add ability to write parquet `_metadata` file
> ------------------------------------------------------
>
> Key: ARROW-1983
> URL: https://issues.apache.org/jira/browse/ARROW-1983
> Project: Apache Arrow
> Issue Type: Improvement
> Components: C++, Python
> Reporter: Jim Crist
> Priority: Major
> Labels: beginner, parquet, pull-request-available
> Fix For: 0.14.0
>
> Time Spent: 6.5h
> Remaining Estimate: 0h
>
> Currently {{pyarrow.parquet}} can only write the {{_common_metadata}} file
> (mostly just schema information). It would be useful to add the ability to
> write a {{_metadata}} file as well. This should include information about
> each row group in the dataset, including summary statistics. Having this
> summary file would allow filtering of row groups without needing to access
> each file beforehand.
> This would require that the user is able to get the written RowGroups out of
> a {{pyarrow.parquet.write_table}} call and then give these objects as a list
> to new function that then passes them on as C++ objects to {{parquet-cpp}}
> that generates the respective {{_metadata}} file.
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