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Deleting an history should cancel running workflow invocations #10442
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We do cancel new scheduling iterations because of deleted histories (https://github.com/galaxyproject/galaxy/blob/dev/lib/galaxy/workflow/run.py#L170). So this must be within a scheduling iteration I assume. I'm nervous about simply rechecking the history between each step, between each job, etc... but clearly scheduling iterations are too long right now if this is a problem. I assume the jobs don't run at least? |
Yes, the user deleted the history while a very large mapping step was being scheduled.
I didn't check at the time if the jobs were run (I have separate workflow and job handlers), and now this is too buried in the logs for me to be confident in the answer, unfortunately. But, as you mention, the unnecessary workflow scheduling of such large steps is any way a problem for us. A possible set of solutions for this could be:
The use of |
This wouldn't change anything - since the invocation will cancel itself if it is over a deleted history. The problem is this happens in the middle of an invocation scheduling step. I guess we could also check the invocation is cancelled after each step - that might be a slight improvement over repeatedly checking the history. I thought maximum_workflow_jobs_per_scheduling_iteration was working when I implemented it, but it is hard to test and may have regressed. It is worth fixing. Hopefully @mvdbeek's recent job scheduling enhancements will reduce this scope of this problem. The fast we schedule jobs the more we can free resources to do more checking and the less likely conflicts like this will be to occur. |
I'm working on it now, and the test was not executed under pytest because the test method didn't start with |
How do you do so much - you're amazing. Good luck let me know if I can help. |
#10490 restores |
That should be fixed in #16252, which will also cancel the invocation's already scheduled jobs. |
This is especially an issue if the inputs for the workflow are from another non-deleted history, meaning that scheduled jobs won't even be paused.
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