我有2个表-Sales
和Product
。 Sales
可以将产品存储为 Idn 或 Name (旧版设计),并且Type
列指定实际的类型与之相关。 Product
等是一个子表,该子表联接到该表中以获取真实数据。 (在此示例中,Product
是存储 Idn 的表以证明问题所在。)
Sales
|------------|--------------------|----------------|
| Idn | Product Idn/Name | Type |
|------------|--------------------|----------------|
| 1 | 1 | Number |
|------------|--------------------|----- ----------|
| 2 | Colgate | Word |
|------------|--------------------|----------------|
Product (Idn)
|------------|------------------|
| Idn | Some Info |
|------------|------------------|
| 1 | ... |
|------------|------------------|
通常,您不应该在Product Idn
上加入这些表,因为它包含混合数据。但是如果您选择LHS与RHS相匹配的行,则 (1) 可以正常工作。例如,如果Product
是存储 Idn 的表,则以下查询失败:
SELECT * from sales JOIN product on sales.pid = product.idn
但以下查询有效:
SELECT * from sales JOIN product on sales.pid = product.idn WHERE type = 'Number'
这在Python 2 + SQLAlchemy + PyODBC中也可以正常工作。但是,当我在Python 3 + SQLAlchemy + PyODBC中尝试此操作时,它给了我一个数据类型转换错误,并且仅在查询被参数化时发生!
现在,如果我在Python 2中将其设为u'number'
,它也会在那里中断;并且b'number'
在Python 3中有效!我猜测Unicode转换存在一些问题。是否尝试猜测编码并做错了什么?我可以更明确地解决此问题吗?
收到的错误是:
Traceback (most recent call last):
File "reproduce.py", line 59, in <module>
print(cursor.execute(select_parametrized, ('number', 1)).fetchall())
pyodbc.ProgrammingError: ('42000', '[42000] [Microsoft][ODBC Driver 17 for SQL Server][SQL Server]Error converting data type varchar to numeric. (8114) (SQLFetch)
这里可能是问题所在,并且有什么好办法可以避免问题而无需执行convert
之类的事情(因为它在以前的版本中有效)?
以下是可用于重现此问题而没有副作用(需要SQLAlchemy
和PyODBC
)的查询:
import sqlalchemy
import sqlalchemy.orm
create_tables = """
CREATE TABLE products(
idn NUMERIC(9) PRIMARY KEY
);
CREATE TABLE sales(
idn NUMERIC(9) PRIMARY KEY,
pid VARCHAR(50) NOT NULL,
type VARCHAR(10) NOT NULL
);
"""
check_tables_exist = """
SELECT * FROM products;
SELECT * FROM sales;
"""
insert_values = """
INSERT INTO products (idn) values (1);
INSERT INTO sales (idn, pid, type) values (1, 1, 'number');
INSERT INTO sales (idn, pid, type) values (2, 'Colgate', 'word');
"""
select_adhoc = """
SELECT * FROM products
JOIN sales ON products.idn = sales.pid
AND sales.type = 'number'
WHERE products.idn in (1);
"""
select_parametrized = """
SELECT * FROM products
JOIN sales ON products.idn = sales.pid
AND sales.type = ?
WHERE products.idn in (?);
"""
delete_tables = """
DROP TABLE products;
DROP TABLE sales;
"""
engine = sqlalchemy.create_engine('mssql+pyodbc://user:password@dsn')
connection = engine.connect()
cursor = engine.raw_connection().cursor()
Session = sqlalchemy.orm.sessionmaker(bind=connection)
session = Session()
session.execute(create_tables)
try:
session.execute(check_tables_exist)
session.execute(insert_values)
session.commit()
print(cursor.execute(select_adhoc).fetchall())
print(cursor.execute(select_parametrized, ('number', 1)).fetchall())
finally:
session.execute(delete_tables)
session.commit()
1。。这是一个错误的假设。它是偶然的-SQL的执行计划优先考虑此条件,如here所述。当它变成NVARCHAR
时,它并没有这样做。
答案 0 :(得分:2)
SQLAlchemy使用您的非参数化查询(select_adhoc
)生成此SQL脚本:
SELECT * FROM products
JOIN sales ON products.idn = sales.pid
AND sales.type = 'number'
WHERE products.idn in (1);
但是使用参数化查询(select_parametrized
),它会生成以下内容:(我从SQL Server Profiler中进行了检查。)
declare @p1 int
set @p1=NULL
exec sp_prepexec @p1 output,N'@P1 nvarchar(12),@P2 int',N'
SELECT * FROM products
INNER JOIN sales ON products.idn = sales.pid
AND sales.type = @P1
WHERE products.idn in (@P2);
',N'number',1
select @p1
如果您在SQL Server上尝试此操作,则会得到相同的异常:
信息8114,第16级,状态5,第32行 将数据类型varchar转换为数字时出错。
问题出在@P1
参数声明上–它隐式转换为varchar
(sales.type
的类型),从而导致此问题。可能是Python 2生成了varchar吗?
如果您这样更改查询,它将可以正常运行;或者您需要将sales.type
的类型更改为nvarchar
。
select_parametrized = """
SELECT * FROM products
INNER JOIN sales ON products.idn = sales.pid
AND sales.type = CAST(? AS VARCHAR(50))
WHERE products.idn in (?);
"""