Purely theoretically, you could change the log and job tables to be unlogged - and thus avoid WAL for them.
The drawback of this: * the data in those tables will be lost if you pull the plug or kill -9 the primary postgres server * the tables are not available (at all) in replicas - so in case of a fallback, you would have to have a manual data import/export for those tables on fail-over, rather than rely on replicas being "ready to fallback immediately". Or accept data loss. * the data from those tables will not be present in backups I am not 100% sure, but I believe loss of data in both tables is not really catastrophic for Airflow, so maybe it's acceptable risk (but likely you should do a disaster-recovery test to see what happens and how to recover in case, indeed, someone pulls the plug on your postgres server. J, On Mon, Dec 29, 2025 at 7:16 PM Natanel <[email protected]> wrote: > Yes, the problem is the manual deletions, we have tried it, it resulted in > the same exact issue, as the scheduled db procedures which clean up the > rows marked as deleted actually get deleted, and so it takes up storage, > yet it does not solve the WAL problem, the problematic table is actually > not task_instance, it is relatively small, the log and job tables are the > biggest tables (the problem with them is the primary key change required), > by a multiple of 10 (or more, cluster dependant). > > The smaller batches might solve the issue, however, it seems to just delay > the problem a little rather than solve it, as deleting data with a delete > query (especially a lot of data) is not a very light operation, and so I > think that this is the main issue. > > It would be nice if we could use partitions instead, as it is a lighter > operation, and does not require us to maintain a query and manage our db, I > have thought about changing the models, most of the changes are relatively > simple, for some it is just removing the foreign key and relying on ORM > level constraints, for others, it requires adding a pre query to have the > same constrains but I do not like that idea, maybe there is another way to > make airflow "partition-friendly"? > > I can't think of a nice way to do so, maybe it does not exist, as the db > clean is as simple as a delete query gets, yet when there is a lot of data, > it is all duplicated in WALs. > > On Mon, Dec 29, 2025, 19:40 Daniel Standish via dev < > [email protected]> > wrote: > > > Have you looked at doing manual deletions? I.e. writing your own sql? > > > > The db clean command is probably not "optimal" for all scenarios. > > > > So for example, if the main problem table for you is task_instance, you > > could periodically delete TI records in smaller batches using some > > appropriate index (whether it exists now or you add it). Then maybe you > > would not stress the db as hard. > > > > Airflow isn't designed to use partitions so, you may not get good results > > with that approach. > > > > > > > > On Mon, Dec 29, 2025 at 7:32 AM Natanel <[email protected]> wrote: > > > > > Hello everyone, after having issues with the 'airflow db clean' > command, > > > where due to the amount of dags and tasks that are running every day in > > our > > > deployments, we get a lot of new data every day, which is stored in the > > > database, and when we delete the data, due to the way PGSQL works, the > > > WAL's get replicated to both the archive storage and the main data > > storage > > > of the db instance, which in turn, causes a significant jump in cpu > > usage, > > > ram usage and disk usage, whenever we run the command, which causes all > > > kinds of issues, we even had it once fill up the db storage, and > causing > > > the database to be unresponsive, forcing us to move to our backup > > database, > > > after we haven't ran the command for a few months due to human error. > > > > > > As of now, I know that this is the accepted and widely used way of > > managing > > > the airflow database's size, however, we noticed that it may cause > issues > > > in certain cases, just like in our case, where if the db has not been > > > cleaned up for a while, cleaning it can be problematic. > > > > > > We decided to try and partition the table, and use pgsql's built in > > > retention of partitions, which does not issue a DELETE query, and is > > > lighter and faster, while being simpler to use, however, we have > > > encountered issues due to having Foreign Key constraints in some > tables, > > > having to duplicate such keys and other than forcing code changes (as > the > > > foreign key must include the partitioned key, as the partitioned key > must > > > be part of the primary key), while also having the issue of sqlalchemy > > > breaking once we change the primary key, with the addition of the > > > constraints on the primary key breaking. > > > > > > And in Mysql, due to the foreign keys, it is not possible to partition > > > tables which include them, as it is not supported yet (according to > this > > > < > > > > > > https://dev.mysql.com/doc/refman/8.4/en/partitioning-limitations-storage-engines.html > > > > > > > ). > > > > > > Has anyone else tried to use the databases built in partition retention > > > system instead of the 'airflow db clean' command? > > > > > > Thanks, Natanel. > > > > > >
