I have now been able to successfully remove datasets from disk. After deleting the dataset or history from the front-end interface (as the user), I then run the cleanup scripts as admin:
python ./scripts/cleanup_datasets/cleanup_datasets.py ./universe_wsgi.ini -d 0 -1 $@ >> ./scripts/cleanup_datasets/delete_userless_histories.log
python ./scripts/cleanup_datasets/cleanup_datasets.py ./universe_wsgi.ini -d 0 -2 -r $@ >> ./scripts/cleanup_datasets/purge_histories.log
python ./scripts/cleanup_datasets/cleanup_datasets.py ./universe_wsgi.ini -d 0 -3 -r $@ >> ./scripts/cleanup_datasets/purge_datasets.log
python ./scripts/cleanup_datasets/cleanup_datasets.py ./universe_wsgi.ini -d 0 -5 -r $@ >> ./scripts/cleanup_datasets/purge_folders.log
python ./scripts/cleanup_datasets/cleanup_datasets.py ./universe_wsgi.ini -d 0 -4 -r $@ >> ./scripts/cleanup_datasets/purge_libraries.log
python ./scripts/cleanup_datasets/cleanup_datasets.py ./universe_wsgi.ini -d 0 -6 -r $@ >> ./scripts/cleanup_datasets/delete_datasets.log
However, my final goal is to have a process that can remove old datasets from disk regardless of whether or not the users have deleted them at the front-end (and then automate said process via cronjob). This will be essentially in a situation where users are likely to leave datasets unattended and accumulating disk space.
I found the following Galaxy thread:
And am trying to use the script it mentions:
python ./scripts/cleanup_datasets/admin_cleanup_datasets.py universe_wsgi.ini -d 30 --smtp <smtp server> --fromaddr rsanka@jcvi.org
I chose –d 30 to remove all datasets older than 30 days, which currently only targets one dataset. The resulting stdout indicates success:
"""""""""""""""""""""""""""""""""""""
# 2014-03-25 16:27:47 - Handling stuff older than 30 days
Marked HistoryDatasetAssociation id 301 as deleted
From: rsanka@jcvi.org
To: isingh@jcvi.org
Subject: Galaxy Server Cleanup - 1 datasets DELETED
----------
Galaxy Server Cleanup
---------------------
The following datasets you own on Galaxy are older than 30 days and have been DELETED:
"Small.fastq" in history "Unnamed history"
You may be able to undelete them by logging into Galaxy, navigating to the appropriate history, selecting "Include Deleted Datasets" from the history options menu, and clicking on the link to undelete each dataset that you want to keep. You can then download the datasets. Thank you for your understanding and cooporation in this necessary cleanup in order to keep the Galaxy resource available. Please don't hesitate to contact us if you have any questions.
-- Galaxy Administrators
Marked 1 dataset instances as deleted
"""""""""""""""""""""""""""""""""""""
But when I check the database, the status of dataset 301 is unchanged (ok-false-false-true).
I then run the same cleanup_datasets.py routine from above (but with –d 30), but dataset 301 is still present. I tried a second time, this time using –d 0, but still no deletion (which is not surprising since the dataset's deleted status is still false).
If I run admin_cleanup_datasets.py again with the same parameters, the stdout says no datasets matched the criteria, so it seems to remember it's previous execution, but it's NOT actually updating the database.
What am I doing wrong?
----------------------------------------------
Ravi Sanka
ICS – Sr. Bioinformatics Engineer
J. Craig Venter Institute
301-795-7743
----------------------------------------------
The cleanup scripts enforce a sort of "lifetime" for the datasets.
The first time they're run, they may mark a dataset as deleted and also reset the update time and you'll have to wait N days for the next stage of the lifetime.
The next time they're run, or if a dataset has already been marked as deleted, the actual file removal happens and purged is set to true (if it wasn't already).
You can manually pass in '-d 0' to force removal of datasets recently marked as deleted.
The purge scripts do not check 'allow_user_dataset_purge', of course.