This commit changes the logic around selecting jobs to run. Before this,
Boundary used a view "job_jobs_to_run" which was a collation of all jobs
that were not running and scheduled to run. When jobs were requested to
run, Boundary would look at this view, grab a certain amount of jobs and
insert them into the "job_run" table. Importantly, while the amount of
jobs to be scheduled at once defaulted to 1 in the scheduler package,
this was entirely overriden in the controller package to -1 (no limit,
run all jobs that the query would return).
With this commit, Boundary now looks at the "job" table directly for
jobs to run, regardless of job run status. This was done to improve DB
performance as the view (which queried all "job_run" rows) was causing
significant DB contention.
Additionally, the option to limit job runs is now removed since it was
already hardcoded to -1 and not user-configurable anyways.
Should the need arise to implement this limit again, this will have to
be done in a different way since the new query does not account for
running jobs and limiting the rows returned after jobs are already
running would yield a no-op (the new query inserts nothing into
"job_run" if any given job is already running).
Before this change, upon the completion of a job run, the scheduler
would update a job_run entry with the completed status as well as the
number of objects affected by the run. Additionally, we then had a
cleaner job whose scope was deleting these completed entries from
job_run.
This commit changes this design to drop the cleaner job the and rolls
its functionality directly into the scheduler. Now, when any given job
run is complete, the scheduler will automatically delete it from the
job_run table itself.
In addition, the completed status has been removed as a valid status as
it is not set anymore.
This change follows a decision that given the data in these job_run
entries is already being deleted by the cleaner job, updating its state
when a job completes just to have it deleted is not efficient.
Additionally, no use-case for this data was surfaced.
Hugo