将临时表与SQLAlchemy一起使用

2024-03-28 15:54:32 发布

您现在位置:Python中文网/ 问答频道 /正文

我正在尝试将临时表与SQLAlchemy一起使用,并将其与现有表相连接。这就是我目前所拥有的

engine = db.get_engine(db.app, 'MY_DATABASE')
df = pd.DataFrame({"id": [1, 2, 3], "value": [100, 200, 300], "date": [date.today(), date.today(), date.today()]})
temp_table = db.Table('#temp_table',
                      db.Column('id', db.Integer),
                      db.Column('value', db.Integer),
                      db.Column('date', db.DateTime))
temp_table.create(engine)
df.to_sql(name='tempdb.dbo.#temp_table',
          con=engine,
          if_exists='append',
          index=False)
query = db.session.query(ExistingTable.id).join(temp_table, temp_table.c.id == ExistingTable.id)
out_df = pd.read_sql(query.statement, engine)
temp_table.drop(engine)
return out_df.to_dict('records')

这不会返回任何结果,因为to_sql没有运行的insert语句(我认为这是因为它们是使用sp_prepexec运行的,但我不完全确定)。

然后我试着写出SQL语句(CREATE TABLE #temp_table...INSERT INTO #temp_table...SELECT [id] FROM...),然后运行pd.read_sql(query, engine)。我收到错误信息

This result object does not return rows. It has been closed automatically.

我想这是因为语句不仅仅是SELECT

我如何解决这个问题(两种解决方案都可以,尽管第一种方案更可取,因为它避免了硬编码的SQL)。为了清楚起见,我不能修改现有数据库中的模式这是一个供应商数据库。


Tags: toiddfdbsqltodaydatevalue
2条回答

如果要插入到临时表中的记录数很小/中等,一种可能是使用literal subqueryvalues CTE而不是创建临时表。

# MODEL
class ExistingTable(Base):
    __tablename__ = 'existing_table'
    id = sa.Column(sa.Integer, primary_key=True)
    name = sa.Column(sa.String)
    # ...

假设还要将以下数据插入到temp表中:

# This data retrieved from another database and used for filtering
rows = [
    (1, 100, datetime.date(2017, 1, 1)),
    (3, 300, datetime.date(2017, 3, 1)),
    (5, 500, datetime.date(2017, 5, 1)),
]

创建包含该数据的CTE或子查询:

stmts = [
    # @NOTE: optimization to reduce the size of the statement:
    # make type cast only for first row, for other rows DB engine will infer
    sa.select([
        sa.cast(sa.literal(i), sa.Integer).label("id"),
        sa.cast(sa.literal(v), sa.Integer).label("value"),
        sa.cast(sa.literal(d), sa.DateTime).label("date"),
    ]) if idx == 0 else
    sa.select([sa.literal(i), sa.literal(v), sa.literal(d)])  # no type cast

    for idx, (i, v, d) in enumerate(rows)
]
subquery = sa.union_all(*stmts)

# Choose one option below.
# I personally prefer B because one could reuse the CTE multiple times in the same query
# subquery = subquery.alias("temp_table")  # option A
subquery = subquery.cte(name="temp_table")  # option B

使用所需的联接和筛选器创建最终查询:

query = (
    session
    .query(ExistingTable.id)
    .join(subquery, subquery.c.id == ExistingTable.id)
    # .filter(subquery.c.date >= XXX_DATE)
)

# TEMP: Test result output
for res in query:
    print(res)    

最后,获取pandas数据帧:

out_df = pd.read_sql(query.statement, engine)
result = out_df.to_dict('records')

您可以尝试使用另一个解决方案-进程键控表

A process-keyed table is simply a permanent table that serves as a temp table. To permit processes to use the table simultaneously, the table has an extra column to identify the process. The simplest way to do this is the global variable @@spid (@@spid is the process id in SQL Server).

。。。

One alternative for the process-key is to use a GUID (data type uniqueidentifier).

http://www.sommarskog.se/share_data.html#prockeyed

相关问题 更多 >