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https://issues.apache.org/jira/browse/ARROW-3204?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16745753#comment-16745753
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Javier Luraschi commented on ARROW-3204:
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A few folks working on R and Arrow got together today, we agree that the R
Arrow package should be in CRAN as soon as possible. However, this is likely to
take a few months since we have to first:
# Have an appropriate build process for Windows which Jeroen is leading, see
[rwinlib/arrow|[https://github.com/rwinlib/arrow].]
# Proper appveyor automation. The UrsaLabs team is planning to hire a build
engineer to help, in the meantime, Kirill might be able to help get this going
to make sure Jeroen's work does not regress as Arrow 0.13 gets developed.
# Have an appropriate build process for OS X.
# The Arrow libraries need to get distributed in the official Debian
repository to be allowed in CRAN. Wes mentioned that, Kouhei (hoping I got this
right), might be able to help the project navigate this in the next few months.
So, while we completely agree with you that is imperative that Arrow gets in
CRAN, in the meantime, we could still make use of Arrow in OS X and Linux using
the remotes package (or devtools) by installing the Arrow runtime first,
followed by:
{code:java}
remotes::install_github("apache/arrow", subdir = "r")
{code}
> [R] Release to CRAN
> -------------------
>
> Key: ARROW-3204
> URL: https://issues.apache.org/jira/browse/ARROW-3204
> Project: Apache Arrow
> Issue Type: New Feature
> Components: R
> Reporter: James Lamb
> Priority: Major
>
> As of [ARROW-1325|https://issues.apache.org/jira/browse/ARROW-1325], the
> project contains a minimal working R package that takes advantage of R's
> built-in support for calling C++ code and uses Rcpp for added support.
> Though the exact public interface of the package hasn't been developed yet
> (so this issue may be running before we walk), one major feature in its
> development will be release to [CRAN|https://cran.r-project.org/], the
> official package repository for the R language.
> Completing this story would mean:
> * Getting source code to state where [R CMD
> CHECK|https://www.r-bloggers.com/how-i-learned-to-stop-worrying-and-love-r-cmd-check/]
> passes with 0 ERRORS, 0 WARNINGS, and 0 NOTES
> * Setting up build process for source and precompiled binary packages (see
> [data.table|https://github.com/Rdatatable/data.table] and
> [XGBoost|https://github.com/dmlc/xgboost] as examples of packages that do
> this)
> * Submission to CRAN and acceptance of the first release
>
> Distribution via CRAN would be a much more natural fit for most R users'
> workflows than the current build-from-source workflow, and comes with all the
> other benefits of package managers (e.g. version pegging, easy distribution
> of platform-specific binaries).
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