On Mar 22, 2013, at 4:57 PM, Lance Parsons wrote:

> Nate Coraor wrote:
>> On Mar 22, 2013, at 11:56 AM, Lance Parsons wrote:
>>> I have been running a Galaxy server for our sequencing researchers for a 
>>> while now and it's become increasingly successful. The biggest resource 
>>> challenge for us has been, and continues to be disk space.  As such, I'd 
>>> like to implement some additional cleanup scripts. I thought I run a few 
>>> questions by this list before I got too far into things.
>>> In general, I'm wondering how to implement updates/additions to the cleanup 
>>> system that will be in line with the direction that the Galaxy project is 
>>> headed.  The pgcleanup.py script is the newest piece of code in this area 
>>> (and even adds cleanup of exported histories, which are absent from the 
>>> older cleanup scripts). Also, the pgcleanup.py script uses a 
>>> "cleanup_event" table that I don't believe is used by the older 
>>> cleanup_datasets.py script. However, the new pgcleanup.py script only works 
>>> for Postgres, and worse, only for version 9.1+.  I run my system on RedHat 
>>> (CentOS) and thus we use version 8.4 of Postgres.  Are there plans to 
>>> support other databases or older versions of Postgres?
>> Hi Lance,
>> pgcleanup.py makes extensive use of Writable CTEs, so there is not really a 
>> way to port it to older versions.  For 8.4 or MySQL, you can still use the 
>> older cleanup_datasets.py.
> After looking at it a bit more, I see what you mean.  Are there plans to 
> implement and additional cleanup scripts for non-postgres 9.1 users?  Just 
> curious so I don't reinvent the wheel, I'd be happy to help with existing 
> efforts.

No, there aren't any plans as long as the alternative (cleanup_datasets.py) 
still works for other versions.

>>> I'd like to implement a script to delete (set the deleted flag) for certain 
>>> datasets (e.g. raw data imported from our archive, for old, inactive users, 
>>> etc.).  I'm wondering if it would make sense to try and extend pgcleanup.py 
>>> or cleanup_datasets.py.  Or perhaps it would be best to just implement a 
>>> separate script, though that seems like I'd have to re-implement a lot of 
>>> boilerplate code for configuration reading, connections, logging, etc.   
>>> Any tips on generally acceptable (supported) procedures for marking a 
>>> dataset as deleted?
>> You could probably reuse a lot of the code from either of the cleanup 
>> scripts for this.
> Right.  It seems to make sense to me to focus on the cleanup_datasets.py 
> since that will work for everyone.  I would like to essentially mimic the 
> user deleting a dataset.  I'd then email them to let them know that some old 
> data had been marked for deletion and let the rest of the scripts proceed as 
> normal, cleaning that up if they don't undelete it.
> It looks like I would want to mark the HistoryDatasetAssociations as deleted? 
>  Is that correct?  Would I need to do anything else to simulate the user 
> deleting the dataset?  

That's correct.


> Thanks for the help,
> Lance
>> Thanks,
>> --nate
> -- 
> Lance Parsons - Scientific Programmer
> 134 Carl C. Icahn Laboratory
> Lewis-Sigler Institute for Integrative Genomics
> Princeton University

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