Hello Andreas,
The best approach to handle this is to have a Galaxy administrator upload the files into a library, creating library datasets. Set the following config setting to point to the NFS accessible directory you use to contain the files:
# Directories of files contained in the following directory can be uploaded to a library from the Admin view library_import_dir = /var/opt/galaxy/import
You can set ACCESS permissions on the library to restrict access to specific users, or leave it public to allow anyone to access the library datasets.
Users can import the library datasets into their own histories for analysis - doing this does not create another disk file, but simply a "pointer" to the library dataset's disk file.
Greg Von Kuster Galaxy Development Team
Andreas Kuntzagk wrote:
Hi,
to reduce traffic when importing big dataset into our local galaxy we would like to copy directly from the fileserver (which is accessible from the galaxy server via NFS) into galaxy without moving through the users desktop computer. Is there already such a tool by chance? At a glance I could only find import.py which imports only from a predefined set of files. So if no such tool exist what would be the best starting point? upload.py? For security reasons I would restrict the import to a certain directory. Anything else to keep in mind?
regards, Andreas _______________________________________________ galaxy-user mailing list galaxy-user@bx.psu.edu http://mail.bx.psu.edu/cgi-bin/mailman/listinfo/galaxy-user