在雪花中存储和检索腌制的python对象 [英] Store and retrieve pickled python objects to/from snowflake

问题描述

根据问题，我正尝试将挑选的python对象存储到雪花中，以便以后再次将它们取回。对此的帮助将不胜感激：

as per question, I am trying to store picked python objects to snowflake, to get them back again at a later date. Help on this would be much appreciated:

雪花表定义：

CREATE OR REPLACE TABLE <db>.<schema>.TESTING_MEMORY (
    MODEL_DATETIME DATETIME,
    SCALARS VARIANT
;

Python代码：

import numpy as np
import pandas as pd
import pickle
from datetime import datetime
import snowflake.connector
from snowflake.connector.pandas_tools import write_pandas
from sklearn.preprocessing import StandardScaler

def create_snowflake_connection():
    conn = snowflake.connector.connect(
        user='<username>',
        account='<account>',
        password = '<password>',
        warehouse='<wh>',
        database='<db>',
        role='<role>',
        schema='<schema>'
    )
    
    return conn

memory = {}

np.random.seed(78)
df = pd.DataFrame({
    'x1': np.random.normal(0, 2, 10000),
    'x2': np.random.normal(5, 3, 10000),
    'x3': np.random.normal(-5, 5, 10000)
})

scaler = StandardScaler()
scaler.fit(df)

scaled_df = scaler.transform(df)
scaled_df = pd.DataFrame(scaled_df, columns=['x1', 'x2', 'x3'])


memory['SCALARS'] = pickle.dumps(scaler)
    

ctx = create_snowflake_connection()


# Write to snowflake
db_dat = pd.DataFrame([list(memory.values())], columns=list(memory.keys()))
db_dat.insert(0, 'MODEL_DATETIME', datetime.now().strftime("%Y-%m-%d %H:%M:%S.%f"))
success, nchunks, nrows, _ = write_pandas(conn=ctx, df = db_dat, table_name = 'TESTING_MEMORY')
  
# retreive from snowflake
cur = ctx.cursor()
sql = """
        SELECT hex_encode(SCALARS)
        FROM <db>.<schema>.TESTING_MEMORY
        QUALIFY ROW_NUMBER() OVER (ORDER BY MODEL_DATETIME DESC) = 1
"""
cur.execute(sql) 
returned = cur.fetch_pandas_all() 


cur.close()
ctx.close()

推荐答案

似乎您要放入python byte 对象放入雪花 variant 对您不起作用。

Seems like you're trying to put python byte object into a Snowflake variant which won't work for you.

这个答案很不错与此处的其他答案类似，除了使用 binary varchar 字段来存储base64编码的二进制文件之外， c>输入。从我在某处阅读的内容来看，base64编码比二进制编码大约大30％。

This answer is kind of similar to what the other answer here suggests except, rather than using a varchar field to store base64 encoded binary, use a binary type instead. base64 encoding is around 30% larger than binary from what I've read somewhere.

使用二进制数据类型创建表：

create or replace table testdb.public.test_table (obj binary);

十六进制对腌制的对象进行编码，写入，读回并在其上调用方法：

import pickle
import snowflake.connector

# This is the object we're going to store in Snowflake as binary
class PickleMe:
    def __init__(self, first_name, last_name):
        self.first_name = first_name
        self.last_name = last_name

    def say_hello(self):
        print(f'Hi there, {self.first_name} {self.last_name}')

# Create the object and store it as hex in the 'hex_person' variable
person = PickleMe('John', 'Doe')
hex_person = pickle.dumps(person).hex()

with snowflake.connector.connect(
    user="username",
    password="password",
    account="snowflake_account_deets",
    warehouse="warehouse_name",
) as con:
    # Write pickled object into table as binary
    con.cursor().execute(f"INSERT INTO testdb.public.test_table values(to_binary('{hex_person}', 'HEX'))")

    # Now get the object back and put it into the 'obj' variable
    (obj,) = con.cursor().execute(f"select obj from testdb.public.test_table").fetchone()

    # Deserialise object and call method on it
    person_obj = pickle.loads(obj, encoding='HEX')
    person_obj.say_hello()

上面的输出是

John Doe，您好

Hi there, John Doe

这篇关于在雪花中存储和检索腌制的python对象的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！