I will try this out then, thanks for your help! I assume this works in 0.9
only?
On Thu, Dec 5, 2013 at 7:18 PM, Michael Bayer <mike...@zzzcomputing.com>wrote:
> 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<http://www.postgresql.org/docs/9.3/static/ddl-partitioning.html#DDL-PARTITIONING-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?
>>>>>
>>>>> --
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>>>>
>>>>
>>>
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>>
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