Public bug reported:
We have to discuss how to support versions jump in the upgrade path of
our db schema, like from ("core", 0) to ("core", 2). This becomes even
more important when we reach the next version.
For me there are two solution:
1.) write 'dummy' upgrade scripts, like core_0_2.py, which do not more than
running core_0_1.run() and core_1_2.run() one after another
2.) add some magic to sql._do_schema_upgrade() which automatically tries to
find an upgrade path and run the 'shortest' possible one.
There is an issue with both solutions: right now the upgrade mechanism
is designed in a way that after each data upgrade the schema upgrade is
done. In both solutions the schema upgrade will be done *after* the full
upgrade path. This can be handled by solution 1.) in the sanest possible
way, the downside is that 1.) does not scale well for big numbers of
schema versions around.
Any Ideas?
** Affects: zeitgeist
Importance: Medium
Status: New
** Changed in: zeitgeist
Importance: Undecided => Medium
--
Upgrade of the db schema strategy for version jumps
https://bugs.launchpad.net/bugs/643303
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Status in Zeitgeist Framework: New
Bug description:
We have to discuss how to support versions jump in the upgrade path of our db
schema, like from ("core", 0) to ("core", 2). This becomes even more important
when we reach the next version.
For me there are two solution:
1.) write 'dummy' upgrade scripts, like core_0_2.py, which do not more than
running core_0_1.run() and core_1_2.run() one after another
2.) add some magic to sql._do_schema_upgrade() which automatically tries to
find an upgrade path and run the 'shortest' possible one.
There is an issue with both solutions: right now the upgrade mechanism is
designed in a way that after each data upgrade the schema upgrade is done. In
both solutions the schema upgrade will be done *after* the full upgrade path.
This can be handled by solution 1.) in the sanest possible way, the downside is
that 1.) does not scale well for big numbers of schema versions around.
Any Ideas?
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