On Mon, Oct 16, 2017 at 9:10 AM, Markus Neteler <nete...@osgeo.org> wrote: > > On Oct 15, 2017 9:50 PM, "Markus Metz" <markus.metz.gisw...@gmail.com> wrote: > > On Sun, Oct 15, 2017 at 9:28 PM, Markus Neteler <nete...@osgeo.org> wrote: > > > > > > On Sun, Oct 15, 2017 at 7:47 PM, Markus Metz > > > <markus.metz.gisw...@gmail.com> wrote: > > > > What do you mean with "a more direct GRASS GIS integration" regarding cloud > > > > storage and/or Cloud Optimized GeoTIFF? > > > > > > Well, I tought of r.external and r.external.out. > > > > OK, rephrasing my question: > > > > What do you mean with "a more direct GRASS GIS integration" regarding cloud storage and/or Cloud Optimized GeoTIFF, and regarding reading and writing such data? > > So, my need is to process EO data closest possible where they are stored.
That sounds like you don't need a more direct GRASS GIS integration of cloud storage, but instead are more direct integration of a GRASS installation into cloud storage. > Imagine a huge object storage or bucket or the like which is surrounded by cloud compute instances. Given the data size between some Terabytes up to Petabytes (e.g. Sentinel) I need to minimize whatever data transfer or extra (format) conversion. Assuming a local GRASS db, data transfer increases with remote input to r.external or a remote directory as output for r.external.out. If you want to reduce data transfer, use r.in.gdal/r.out.gdal. If you want to reduce format conversions, use r.external/r.external.out. > > Even's suggestion to use FUSE to mount > buckets in the file system will be something to try. > > However, the location concept is also causing some friction here: Sentinel data are stored in many different zones i.e. would result in many different locations. Would gdalwarp help? Markus M > I have no solution to that yet but this issue plus the need to minimize bandwidth usage is the key for a successful cloud storage based processing. > > So I started with thinking about how to connect to current EO storages. > > Best. > markusN
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