使用 SQLAlchemy 批量更新

Question

我正在使用 SQLAlchemy 1.1.0b 将大量数据批量更新插入到 PostgreSQL 中，我运行遇到了重复键错误。

from sqlalchemy import *
from sqlalchemy.orm import sessionmaker
from sqlalchemy.ext.automap import automap_base

import pg

engine = create_engine("postgresql+pygresql://" + uname + ":" + passw + "@" + url)

# reflectively load the database.
metadata = MetaData()
metadata.reflect(bind=engine)
session = sessionmaker(autocommit=True, autoflush=True)
session.configure(bind=engine)
session = session()
base = automap_base(metadata=metadata)
base.prepare(engine, reflect=True)

table_name = "arbitrary_table_name" # this will always be arbitrary
mapped_table = getattr(base.classses, table_name)
# col and col2 exist in the table.
chunks = [[{"col":"val"},{"col2":"val2"}],[{"col":"val"},{"col2":"val3"}]]

for chunk in chunks:
    session.bulk_insert_mappings(mapped_table, chunk)
    session.commit()

当我运行它时，我得到这个：

sqlalchemy.exc.IntegrityError: (pg.IntegrityError) ERROR:  duplicate key value violates unique constraint <constraint>

我似乎也无法将 mapped_table 正确实例化为 Table() 对象。

我正在处理时间序列数据，因此我正在批量抓取时间范围内有一些重叠的数据。我想做一个批量更新插入以确保数据一致性。

对大型数据集执行批量更新插入的最佳方法是什么？我现在知道 PostgreSQL support upserts，但我不确定如何在 SQLAlchemy 中执行此操作。

Answer 1

来自

After I found this command, I was able to perform upserts, but it is worth mentioning that this operation is slow for a bulk "upsert".

The alternative is to get a list of the primary keys you would like to upsert, and query the database for any matching ids:

使用 SQLAlchemy 批量更新

Bulk upsert with SQLAlchemy

python

postgresql

sqlalchemy

upsert