I have a feeling that making those **two** tables partition-friendly should be easy - and maybe that's all that we need. That would make it possible for you to use the partitioning, (where it would not be necessary for everyone). There might be a few ways of doing it without losing uniqueness. For example Job ID and audit log ID could follow certain conventions - and always start with a partition key) thus providing uniqueness we need.
Those two tables are pretty specific and neither job id nor log id impact anything else in our data model. I think such a change to make those two tables "partition friendly" could be accepted, but we could only say it after seeing a POC. J. On Mon, Dec 29, 2025 at 8:01 PM <[email protected]> wrote: > I do think that the second option is best, it is also what we wanted to > do, the only reason we did not do that is because from our tests, sql > alchemy sometimes breaks as it expects certain constraints which are not > there, mainly for update queries, select works well, if I am not mistaken, > there are 3 or 4 large tables, job being the largest (7 times larger than > the second largest), the question is, will such a pull request be approved? > > As we do lose the unique constraint (as it becomes per partition), though > it is a sequence that most likely won't repeat until the previous has been > deleted, but if not, we might query unrelated job or log data, and so > changes in the api server are also needed, creating the pr is not a > problem, the question is how beneficial will it be, as if it is done to > those problematic tables, it means that the preferred way to manage > retention is from the db, and can be an optional alembic script. > > I do not want to just push a fix that will add more complexity than the > benefit it will bring. > > If we do go the pr way, a separate discussion is probably needed to decide > how it should be done (most likely an additional airflow command to turn on > or off the partitions and retention) > > Doing it as a custom solution has caused problems with sqlalchemy, and we > do not want to do so as if later an alembic script relies on the primary > key in some way, we will need to fix it manually and deal with the problems > it may cause when we update. > > > On 29 Dec 2025, at 21:36, Jarek Potiuk <[email protected]> wrote: > > > > Another option is that you ( could make ONLY for those two tables - > > partition-friendly. And do not partition anything else. I think that > > **could** be possible - both have datetime fields that could be used as > > partition keys - you would have to assess if you can do it as your > "custom" > > solution or whether it would require some changes to airflow models. But > I > > can't see foreign key problems if ONLY those two tables are partitioned, > so > > likely you could do it yourself in your DB. > > > > In this case - maybe "let's solve those tables that are problematic" is > > easier to do than "let's apply partitioning to everything". > > > >> On Mon, Dec 29, 2025 at 7:31 PM Jarek Potiuk <[email protected]> wrote: > >> > >> 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. > >>>>> > >>>> > >>> > >> > > --------------------------------------------------------------------- > To unsubscribe, e-mail: [email protected] > For additional commands, e-mail: [email protected] > >
