Going back even earlier, back in 2011 when I was at Google we funded some
work on bringing 64-bit integers into R:

  https://opensource.googleblog.com/2011/11/bringing-64-bit-data-to-r.html

Some of the use cases were language interop, differentiating between 64-bit
quantities used as identifiers efficiently, etc.

Around that time I also submitted a patch we had for a few releases of R to
prevent 2^53 == 2^53 + 1 from returning TRUE which was unfortunately backed
out of a later release of R.

        - Murray


On Mon, Aug 3, 2026 at 9:05 AM Brian Repko <[email protected]>
wrote:

>
> I just joined the listserv so apologies if this is not threaded in the
> original discussion
> https://stat.ethz.ch/pipermail/r-devel/2026-July/084631.html
>
> A restating of the use cases from Kevin Ushey:
>  1. Language interop - C/C++/Fortran, Python via reticulate, Java via
> rJava, Javascript / JSON APIs
>  2. Data structure interop - arrow, DBI (BIGINT), parquet, hdf5, zarr
> There are use cases in both single-cell / spatial transcriptomics - big
> sparse array where we need interop above or the ability to handle more than
> 2^53-1.
>
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>
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> https://stat.ethz.ch/mailman/listinfo/r-devel
>

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