[R-sig-Geo] BIG DATABASE

[Javier Moreira]

Can I use this answer to ask exactly for what it's mentioned.
R and Postgis mostly for Easter files.
Can you point books, online courses, tutorials, GitHub pages, anything, to
better understand this?
I had been struggling to find info.

Thanks!

El vie., 25 may. 2018 1:35, Tom Philippi <tephilippi using gmail.com> escribió:

> What Roger said (as always).
>
> Note that if you use tidyverse and magrittr, dplyr and tidyverse tools work
> well with databases via DBI.  sqldf also works with multiple SQL database
> backends if you're an ol dog like me and don't use tidyverse much.
>
> Also, since this is r-sig-*GEO*, note that postgreSQL has postGIS for
> spatial data, which does far more than the automatic tiling of large
> rasters in package raster.  I'm seeing wonderful performance working with a
> 340M observation >100GB dataset of bird observation data in R via postGIS,
> even with "only" 32GB RAM and constrained to running win7, not linux/unix.
>
> One alternative is that if your database is running on massive hardware
> (tons of memory, many cores, etc.), it is possible to run R within both
> postgreSQL and now MS SQL Server, the first free, the second an additional
> cost add-on, and both usually at the cost of painful negotiations with DA
> administrators for permissions to run your ad hoc R code on their SQL
> server.  If you have the hardware, you can even run R with hadoop, although
> I've never done that with spatial data.
>
> Tom 0
>
>
> On Thu, May 24, 2018 at 5:04 AM, Roger Bivand <Roger.Bivand using nhh.no> wrote:
>
> > On Thu, 24 May 2018, Yaya Bamba wrote:
> >
> > Thanks to all of you. I will try with the package  RMySQL and see.
> >>
> >
> > Maybe look more generally through the packages depending on and importing
> > from DBI (https://cran.r-project.org/package=DBI) to see what is
> > available - there are many more than RMySQL.
> >
> > and use the Official Statistics and HPC Task Views:
> >
> > https://cran.r-project.org/view=OfficialStatistics
> >
> > https://cran.r-project.org/view=HighPerformanceComputing
> >
> > to see how typical workflows (not necessarily DB-based) can be handled.
> > The HPC TV has a section on large memory and out-of-memory approaches. If
> > your data are spatial in raster format, the raster package provides some
> > out-of-memory functionality. In sf, spatial vector data may be read from
> > databases too.
> >
> > Roger
> >
> >
> >
> >> 2018-05-24 11:33 GMT+00:00 Andres Diaz Loaiza <madiazl using gmail.com>:
> >>
> >> Hello Yaya,
> >>>
> >>> Many years ago I work with a database in MySQL connected to R through
> the
> >>> package RMySQL​. The data was stored in the MySQL and I was connecting
> >>> and
> >>> using the data from R
> >>>
> >>> you should have a look in:
> >>>
> >>> https://cran.r-project.org/web/packages/RMySQL/index.html
> >>>
> >>> Cheers,
> >>>
> >>> Andres
> >>>
> >>>
> >>
> >>
> >>
> >>
> > --
> > Roger Bivand
> > Department of Economics, Norwegian School of Economics,
> > Helleveien 30, N-5045 Bergen, Norway.
> > voice: +47 55 95 93 55; e-mail: Roger.Bivand using nhh.no
> > http://orcid.org/0000-0003-2392-6140
> > https://scholar.google.no/citations?user=AWeghB0AAAAJ&hl=en
> > _______________________________________________
> > R-sig-Geo mailing list
> > R-sig-Geo using r-project.org
> > https://stat.ethz.ch/mailman/listinfo/r-sig-geo
> >
> >
>
>         [[alternative HTML version deleted]]
>
> _______________________________________________
> R-sig-Geo mailing list
> R-sig-Geo using r-project.org
> https://stat.ethz.ch/mailman/listinfo/r-sig-geo
>

	[[alternative HTML version deleted]]