[R] About performance of R
Duncan Murdoch
murdoch.duncan at gmail.com
Wed May 27 20:52:19 CEST 2015
On 27/05/2015 11:00 AM, Suman wrote:
> Hi there,
>
> Now that R has grown up with a vibrant community. It's no 1 statistical package used by scientists. It's graphics capabilities are amazing.
> Now it's time to provide native support in "R core" for distributed and parallel computing for high performance in massive datasets.
> And may be base R functions should be replaced with best R packages like data.table, dplyr, reader for fast and efficient operations.
Given your first three sentences, I would say the current development
strategy for R is successful. As Bert mentioned, one thing we have
always tried to do is to make improvements without large disruptions to
the existing code base. I think we will continue to do that.
This means we are unlikely to make big, incompatible replacements. But
there's nothing stopping people from using data.table, dplyr, etc. even
if they aren't in the core. In fact, having them outside of core R is
better: there are only so many core R developers, and if they are
working on data.table, etc., they wouldn't be working on other things.
Compatible replacements are another question. There is ongoing work on
making R faster, and making it easier to take advantage of multiple
processors. I believe R 3.2.0 is faster than the R 3.1.x series in many
things, and changes like that are likely to continue. Plus, there is
base support for explicit parallel programming in the parallel package,
as Jeff mentioned.
As to David and his large bundles; those would definitely be appreciated.
Duncan Murdoch
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