With the example I gave, when accessing .partitioned on a First instance, the lazy loader will convert all columns from “First” into a bound parameter, it emits this:
SELECT partitioned.other_id AS partitioned_other_id, second.other_id AS
second_other_id, partitioned.partition_key AS partitioned_partition_key,
second.first_id AS second_first_id
FROM partitioned JOIN second ON partitioned.other_id = second.other_id
WHERE ? = partitioned.partition_key AND ? = second.first_id
2013-12-05 14:14:42,689 INFO sqlalchemy.engine.base.Engine (u'p1', 2)
“first.partition_key” is not in the query, it’s replaced by ‘p1’ in this case,
the value that was assigned to that First instance. There is no “secondary”
table per se in the example I gave.
On Dec 5, 2013, at 1:55 PM, Adrian Schreyer <adrian.schre...@gmail.com> wrote:
> The partitioned relationship actually referred to the tertiary table in both
> the primary and secondary join - the problem for me was that in the
> primaryjoin
>
>
> primaryjoin="and_(First.first_id==Second.first_id,
> First.partition_key==Partitioned.partition_key)"
> only First.first_id will be interpolated with the actual value first_id of
> the instance in question whereas First.partition_key on the other hand will
> be interpolated as column object. The problem is that in this case
> First.partition_key has to be interpolated with the actual value to get the
> constraint-exclusion to work. In a normal many-to-many relationship this
> would not be necessary and maybe that is why it only interpolates the values
> for the join on the secondary table.
>
> The partitioned relationship emits a query like this if the attribute is
> accessed:
>
>
> SELECT partitioned.*
> FROM partitioned, second, first
> WHERE %(param_1)s = second.first_id
> AND first.partition_key = partitioned.partition_key
> AND second.other_id = partitioned.other_id
> But I would need first.partitioned_key to be %(param_2)s.
>
> So far I used a @property around a query function to add the partition_key to
> query.filter() manually.
>
>
>
> On Thu, Dec 5, 2013 at 4:37 PM, Michael Bayer <mike...@zzzcomputing.com>
> wrote:
> oh, you want to refer to the tertiary table in both the primary and secondary
> join. so right this pattern does not correspond to the A->secondary->B
> pattern and isn’t really a classic many-to-many.
>
> a quick way to map these are to use non primary mappers (was going to just
> paraphrase, but let me just try it out b.c. these are fun anyway, and I want
> to see the new joining behavior we have in 0.9…):
>
> from sqlalchemy import *
> from sqlalchemy.orm import *
> from sqlalchemy.ext.declarative import declarative_base
>
> Base = declarative_base()
>
> class First(Base):
> __tablename__ = 'first'
>
> first_id = Column(Integer, primary_key=True)
> partition_key = Column(String)
>
> def __repr__(self):
> return ("First(%s, %s)" % (self.first_id, self.partition_key))
>
> class Second(Base):
> __tablename__ = 'second'
>
> id = Column(Integer, primary_key=True)
> first_id = Column(Integer)
> other_id = Column(Integer)
>
> class Partitioned(Base):
> __tablename__ = 'partitioned'
>
> id = Column(Integer, primary_key=True)
> partition_key = Column(String)
> other_id = Column(Integer)
>
> def __repr__(self):
> return ("Partitioned(%s, %s)" % (self.partition_key, self.other_id))
>
>
> j = join(Partitioned, Second, Partitioned.other_id == Second.other_id)
>
> partitioned_second = mapper(Partitioned, j, non_primary=True, properties={
> # note we need to disambiguate columns here - the join()
> # will provide them as j.c.<tablename>_<colname> for access,
> # but they retain their real names in the mapping
> "id": j.c.partitioned_id,
> "other_id": [j.c.partitioned_other_id, j.c.second_other_id],
> "secondary_id": j.c.second_id
> })
>
> First.partitioned = relationship(
> partitioned_second,
> primaryjoin=and_(
> First.partition_key ==
> partitioned_second.c.partition_key,
> First.first_id ==
> foreign(partitioned_second.c.first_id)
> ), innerjoin=True)
>
> e = create_engine("postgresql://scott:tiger@localhost/test", echo=True)
> Base.metadata.drop_all(e)
> Base.metadata.create_all(e)
> s = Session(e)
> s.add_all([
> First(first_id=1, partition_key='p1'),
> First(first_id=2, partition_key='p1'),
> First(first_id=3, partition_key='p2'),
> Second(first_id=1, other_id=1),
> Second(first_id=2, other_id=1),
> Second(first_id=3, other_id=2),
> Partitioned(partition_key='p1', other_id=1),
> Partitioned(partition_key='p1', other_id=2),
> Partitioned(partition_key='p2', other_id=2),
> ])
> s.commit()
>
> for row in s.query(First, Partitioned).join(First.partitioned):
> print(row)
>
> for f in s.query(First):
> for p in f.partitioned:
> print(f.partition_key, p.partition_key)
>
>
> I mapped to a join directly, and not a select, so as long as we aren’t using
> SQLite (and are using 0.9) we get nested join behavior like this:
>
> SELECT first.first_id AS first_first_id, first.partition_key AS
> first_partition_key, partitioned.id AS partitioned_id,
> partitioned.partition_key AS partitioned_partition_key, partitioned.other_id
> AS partitioned_other_id
> FROM first JOIN (partitioned JOIN second ON partitioned.other_id =
> second.other_id) ON first.partition_key = partitioned.partition_key AND
> first.first_id = second.first_id
> 2013-12-05 11:27:18,347 INFO sqlalchemy.engine.base.Engine {}
> (First(1, p1), Partitioned(p1, 1))
> (First(2, p1), Partitioned(p1, 1))
> (First(3, p2), Partitioned(p2, 2))
>
>
> the load of f.partitioned will load the Partitioned objects in terms of the
> “partitioned_second” mapper, so those objects will have those extra cols from
> “second” on them. You can screw around with this using exclude_properties
> for those cols you don’t need to refer to on the mapping, and perhaps
> primary_key if the mapper complains, such as:
>
> partitioned_second = mapper(Partitioned, j, non_primary=True, properties={
> "id": j.c.partitioned_id,
> "other_id": [j.c.partitioned_other_id, j.c.second_other_id],
> }, exclude_properties=[j.c.second_id], primary_key=[j.c.partitioned_id,
> j.c.second_other_id])
>
> or you can just ignore those extra attributes on some of your Partitioned
> objects.
>
>
>
>
>
>
>
>
> On Dec 5, 2013, at 11:03 AM, Adrian Schreyer <adrian.schre...@gmail.com>
> wrote:
>
>> Given the three mappings First, Second and Partitioned, I want to declare a
>> relationship between First and Partitioned. The problem is that Partitioned
>> is partitioned by partition_key which is a column in First but not in
>> Second. Second however contains the identifier that actually links First to
>> specific rows in the partitioned table.
>>
>> So far the mapping looks like this mock example:
>>
>>
>> partitioned = relationship("Partitioned",
>> secondary=Base.metadata.tables['schema.seconds'],
>> primaryjoin="and_(First.first_id==Second.first_id,
>> First.partition_key==Partitioned.partition_key)",
>> secondaryjoin="Second.other_id==Partitioned.other_id",
>> foreign_keys="[Second.first_id, Partitioned.partition_key,
>> Partitioned.other_id]",
>> uselist=True, innerjoin=True, lazy='dynamic')
>> It works, but it only interpolates the First.first_id with the actual value
>> which normally makes sense but to make the PostgreSQL constraint-exclusion
>> work the First.partition_key would need to be interpolated with the proper
>> value as well. Right now it is only given as
>> First.partition_key==Partitioned.partition_key.
>>
>> Does that make sense? I am not sure if my relationship configuration is
>> wrong or if this kind of mapping is simply not supported.
>>
>>
>>
>> On Thu, Dec 5, 2013 at 3:31 PM, Michael Bayer <mike...@zzzcomputing.com>
>> wrote:
>>
>> On Dec 5, 2013, at 6:57 AM, Adrian Schreyer <adrian.schre...@gmail.com>
>> wrote:
>>
>>> Actually that was a bit too early but I tracked the problem down to the
>>> many-to-many relationship. Parameters are only interpolated (e.g.
>>> %(param_1)s) for the primaryjoin to the secondary table. Is there a
>>> technique to force relationship() to interpolate a parameter between the
>>> 1st and 3rd table instead of using only table.column=table.column?
>>
>> there’s no reason why that would be the case can you provide more specifics?
>>
>>
>>
>>
>>>
>>>
>>> On Thu, Dec 5, 2013 at 10:58 AM, Adrian Schreyer
>>> <adrian.schre...@gmail.com> wrote:
>>> Never mind,
>>>
>>> the problem was that I specified the clause in a secondaryjoin and not in
>>> the primaryjoin of the relationship().
>>>
>>>
>>> On Thu, Dec 5, 2013 at 10:44 AM, Adrian <adrian.schre...@gmail.com> wrote:
>>> Hi All,
>>>
>>> I have a few partitioned tables in my PostgreSQL database but I do not know
>>> yet how to make the ORM relationship() with partition constraint-exclusion
>>> on the instance level. Constraint-exclusion does not work with joins and
>>> requires scalar values - the problem is that I would need to add an
>>> additional WHERE clause to the primaryjoin (which adds the partition key)
>>> if the relationship is accessed from the instance level, e.g.
>>> user.addresses. Is there a mechanism in relationship() to distinguish
>>> between class-based joins (User.addresses) and instance-level access?
>>>
>>> --
>>> You received this message because you are subscribed to a topic in the
>>> Google Groups "sqlalchemy" group.
>>> To unsubscribe from this topic, visit
>>> https://groups.google.com/d/topic/sqlalchemy/ov-mYWA7XAM/unsubscribe.
>>> To unsubscribe from this group and all its topics, send an email to
>>> sqlalchemy+unsubscr...@googlegroups.com.
>>> To post to this group, send email to sqlalchemy@googlegroups.com.
>>> Visit this group at http://groups.google.com/group/sqlalchemy.
>>> For more options, visit https://groups.google.com/groups/opt_out.
>>>
>>>
>>>
>>> --
>>> You received this message because you are subscribed to the Google Groups
>>> "sqlalchemy" group.
>>> To unsubscribe from this group and stop receiving emails from it, send an
>>> email to sqlalchemy+unsubscr...@googlegroups.com.
>>>
>>> To post to this group, send email to sqlalchemy@googlegroups.com.
>>> Visit this group at http://groups.google.com/group/sqlalchemy.
>>> For more options, visit https://groups.google.com/groups/opt_out.
>>
>>
>>
>> --
>> You received this message because you are subscribed to the Google Groups
>> "sqlalchemy" group.
>> To unsubscribe from this group and stop receiving emails from it, send an
>> email to sqlalchemy+unsubscr...@googlegroups.com.
>> To post to this group, send email to sqlalchemy@googlegroups.com.
>> Visit this group at http://groups.google.com/group/sqlalchemy.
>> For more options, visit https://groups.google.com/groups/opt_out.
>
>
>
> --
> You received this message because you are subscribed to the Google Groups
> "sqlalchemy" group.
> To unsubscribe from this group and stop receiving emails from it, send an
> email to sqlalchemy+unsubscr...@googlegroups.com.
> To post to this group, send email to sqlalchemy@googlegroups.com.
> Visit this group at http://groups.google.com/group/sqlalchemy.
> For more options, visit https://groups.google.com/groups/opt_out.
signature.asc
Description: Message signed with OpenPGP using GPGMail
