使用SQLAlchemy批量上传 [英] Bulk upsert with SQLAlchemy

问题描述

我正在使用SQLAlchemy 1.1.0b将大量数据批量上传到PostgreSQL中，并且遇到了重复的关键错误。

I am working on bulk upserting lots of data into PostgreSQL with SQLAlchemy 1.1.0b, and I'm running into duplicate key errors.

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()

运行它时，我会得到：

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

我似乎无法正确实例化 mapped_table 作为 Table（）对象。

I can't seem to properly instantiate the mapped_table as a Table() object, either.

我正在处理时间序列数据，所以我我正在大量时间范围内重叠地获取数据。我想进行批量增补，以确保数据的一致性。

I'm working with time series data, so I'm grabbing data in bulk with some overlap in time ranges. I want to do a bulk upsert to ensure data consistency.

对大型数据集进行批量增补的最佳方法是什么？我知道现在 PostgreSQL支持upserts ，但是我不确定如何在SQLAlchemy中执行此操作。

What's the best way to do a bulk upsert with a large data set? I know PostgreSQL support upserts now, but I'm not sure how to do this in SQLAlchemy.

推荐答案

来自https://stackoverflow.com/a/26018934/465974

此命令可以执行upsert，但是值得一提的是
，对于批量 upsert而言，此操作很慢。

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".

获取您想要
upsert的主键的列表，并在数据库中查询任何匹配的id：

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

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