[openstack-dev] [Nova] Handling soft delete for instance rows in a new cells database

Andrew Laski andrew.laski at rackspace.com
Wed Nov 26 15:40:32 UTC 2014

On 11/25/2014 11:54 AM, Solly Ross wrote:
>> I can't comment on other projects, but Nova definitely needs the soft
>> delete in the main nova database. Perhaps not for every table, but
>> there is definitely code in the code base which uses it right now.
>> Search for read_deleted=True if you're curious.
> Just to save people a bit of time, it's actually `read_deleted='yes'`
> or `read_deleted="yes"` for many cases.
> Just to give people a quick overview:
> A cursory glance (no pun intended) seems to indicate that quite a few of
> these are reading potentially deleted flavors.  For this case, it makes
> sense to keep things in one table (as we do).
> There are also quite a few that seem to be making sure deleted "things"
> are properly cleaned up.  In this case, 'deleted' acts as a "CLEANUP"
> state, so it makes just as much sense to keep the deleted rows in a
> separate table.
>> For this case in particular, the concern is that operators might need
>> to find where an instance was running once it is deleted to be able to
>> diagnose issues reported by users. I think that's a valid use case of
>> this particular data.
>>>> This is a new database, so its our big chance to get this right. So,
>>>> ideas welcome...
>>>> Some initial proposals:
>>>> - we do what we do in the current nova database -- we have a deleted
>>>> column, and we set it to true when we delete the instance.
>>>> - we have shadow tables and we move delete rows to a shadow table.
>>> Both approaches are viable, but as the soft-delete column is widespread, it
>>> would be thorny for this new app to use some totally different scheme,
>>> unless the notion is that all schemes should move to the audit table
>>> approach (which I wouldn’t mind, but it would be a big job).    FTR, the
>>> audit table approach is usually what I prefer for greenfield development,
>>> if all that’s needed is forensic capabilities at the database inspection
>>> level, and not as much active GUI-based “deleted” flags.   That is, if you
>>> really don’t need to query the history tables very often except when
>>> debugging an issue offline.  The reason its preferable is because those
>>> rows are still “deleted” from your main table, and they don’t get in the
>>> way of querying.   But if you need to refer to these history rows in
>>> context of the application, that means you need to get them mapped in such
>>> a way that they behave like the primary rows, which overall is a more
>>> difficult approach than just using the soft delete column.
> I think it does really come down here to how you intend to use the soft-delete
> functionality in Cells.  If you just are using it to debug or audit, then I think
> the right way to go would be either the audit table (potentially can store more
> lifecycle data, but could end up taking up more space) or a separate shadow
> table (takes up less space).
> If you are going to use the soft delete for application functionality, I would
> consider differentiating between "deleted" and "we still have things left to
> clean up", since this seems to be mixing two different requirements into one.

The case that spawned this discussion is one where deleted rows are not 
needed for application functionality.  So I'm going to update the 
proposed schema there to not include a 'deleted' column. Fortunately 
there's still some time before the question of how to handle deletes 
needs to be fully sorted out.

>>> That said, I have a lot of plans to send improvements down the way of the
>>> existing approach of “soft delete column” into projects, from the querying
>>> POV, so that criteria to filter out soft delete can be done in a much more
>>> robust fashion (see
>>> https://bitbucket.org/zzzeek/sqlalchemy/issue/3225/query-heuristic-inspector-event).
>>> But this is still more complex and less performant than if the rows are
>>> just gone totally, off in a history table somewhere (again, provided you
>>> really don’t need to look at those history rows in an application context,
>>> otherwise it gets all complicated again).
>> Interesting. I hadn't seen consistency between the two databases as
>> trumping doing this less horribly, but it sounds like its more of a
>> thing that I thought.
>> Thanks,
>> Michael
>> --
>> Rackspace Australia
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