例如,我有Parcel
模型,其sender
和receiver
都是Subject
。
我试图从特定发件人那里获得包裹。我不想使用Parcel.sender.has()
,因为性能,我真正的桌子太大了。
来自docs:
因为has()使用了相关的子查询,所以与大型目标表相比,它的性能与使用连接时的表现差不多。
以下是完整的粘贴并运行示例:
from sqlalchemy import create_engine, Column, Integer, Text, ForeignKey
from sqlalchemy.orm import sessionmaker, relationship
from sqlalchemy.ext.declarative.api import declarative_base
from sqlalchemy.orm.util import aliased
engine = create_engine('sqlite://')
Session = sessionmaker(bind=engine)
s = Session()
Base = declarative_base()
class Subject(Base):
__tablename__ = 'subject'
id = Column(Integer, primary_key=True)
name = Column(Text)
class Parcel(Base):
__tablename__ = 'parcel'
id = Column(Integer, primary_key=True)
sender_id = Column(Integer, ForeignKey('subject.id'))
receiver_id = Column(Integer, ForeignKey('subject.id'))
sender = relationship('Subject', foreign_keys=[sender_id], uselist=False, lazy='joined')
receiver = relationship('Subject', foreign_keys=[receiver_id], uselist=False, lazy='joined')
def __repr__(self):
return '<Parcel #{id} {s} -> {r}>'.format(id=self.id, s=self.sender.name, r=self.receiver.name)
# filling database
Base.metadata.create_all(engine)
p = Parcel()
p.sender, p.receiver = Subject(name='Bob'), Subject(name='Alice')
s.add(p)
s.flush()
#
# Method #1 - using `has` method - working but slow
print(s.query(Parcel).filter(Parcel.sender.has(name='Bob')).all())
所以,我试图通过别名关系加入和过滤,这引发了一个错误:
#
# Method #2 - using aliased joining - doesn't work
# I'm getting next error:
#
# sqlalchemy.exc.InvalidRequestError: Could not find a FROM clause to join from.
# Tried joining to <AliasedClass at 0x7f24b7adef98; Subject>, but got:
# Can't determine join between 'parcel' and '%(139795676758928 subject)s';
# tables have more than one foreign key constraint relationship between them.
# Please specify the 'onclause' of this join explicitly.
#
sender = aliased(Parcel.sender)
print(s.query(Parcel).join(sender).filter(sender.name == 'Bob').all())
我发现如果我使用连接条件而不是关系来指定模型,它就会起作用。但最终的SQL查询是我所期望的:
print(
s.query(Parcel)\
.join(Subject, Parcel.sender_id == Subject.id)\
.filter(Subject.name == 'Bob')
)
生成下一个SQL查询:
SELECT parcel.id AS parcel_id,
parcel.sender_id AS parcel_sender_id,
parcel.receiver_id AS parcel_receiver_id,
subject_1.id AS subject_1_id,
subject_1.name AS subject_1_name,
subject_2.id AS subject_2_id,
subject_2.name AS subject_2_name
FROM parcel
JOIN subject ON parcel.sender_id = subject.id
LEFT OUTER JOIN subject AS subject_1 ON subject_1.id = parcel.sender_id
LEFT OUTER JOIN subject AS subject_2 ON subject_2.id = parcel.receiver_id
WHERE subject.name = ?
在这里,您可以看到subject
表正在连接三次而不是两次。这是因为sender
和receiver
关系都配置为加载加入。第三次加入是我过滤的主题。
我希望最终查询看起来像这样:
SELECT parcel.id AS parcel_id,
parcel.sender_id AS parcel_sender_id,
parcel.receiver_id AS parcel_receiver_id,
subject_1.id AS subject_1_id,
subject_1.name AS subject_1_name,
subject_2.id AS subject_2_id,
subject_2.name AS subject_2_name
FROM parcel
LEFT OUTER JOIN subject AS subject_1 ON subject_1.id = parcel.sender_id
LEFT OUTER JOIN subject AS subject_2 ON subject_2.id = parcel.receiver_id
WHERE subject_1.name = ?
我认为通过多个引用关系进行过滤不应该如此不清楚,并且有更好更清晰的方法。请帮我找到。
答案 0 :(得分:1)
您已对其进行了配置,sender
和reciever
将始终通过加入加入。
您可以更改它并手动执行joinedload
,当您实际需要同时加入两个连接时加载它们。
如果您希望保留定义,可以“帮助”SQLAlchemy并指出查询已经包含了此比较的所有数据,并且不需要额外的连接。为此,使用contains_eager
选项。
修改后的查询:
q = (s.query(Parcel)
.join(Parcel.sender)
.options(contains_eager(Parcel.sender))
.filter(Subject.name == 'Bob'))
它产生的SQL:
SELECT subject.id AS subject_id,
subject.name AS subject_name,
parcel.id AS parcel_id,
parcel.sender_id AS parcel_sender_id,
parcel.receiver_id AS parcel_receiver_id,
subject_1.id AS subject_1_id,
subject_1.name AS subject_1_name
FROM parcel
JOIN subject ON subject.id = parcel.sender_id
LEFT OUTER JOIN subject AS subject_1 ON subject_1.id = parcel.receiver_id
WHERE subject.name = ?