如何使用 pyarrow 将 Pandas 数据帧设置/获取到 Redis [英] How to set/get Pandas dataframes into Redis using pyarrow

问题描述

使用

dd = {'ID': ['H576','H577','H578','H600', 'H700'],
      'CD': ['AAAAAAA', 'BBBBB', 'CCCCCC','DDDDDD', 'EEEEEEE']}
df = pd.DataFrame(dd)

Pandas 0.25 之前的版本，这在下面起作用了.

Pre Pandas 0.25, this below worked.

set:  redisConn.set("key", df.to_msgpack(compress='zlib'))
get:  pd.read_msgpack(redisConn.get("key"))

现在，有已弃用的警告..

Now, there are deprecated warnings..

FutureWarning: to_msgpack is deprecated and will be removed in a future version.
It is recommended to use pyarrow for on-the-wire transmission of pandas objects.

The read_msgpack is deprecated and will be removed in a future version.
It is recommended to use pyarrow for on-the-wire transmission of pandas objects.

pyarrow 是如何工作的?而且，我如何将 pyarrow 对象传入和传回 Redis.

How does pyarrow work? And, how do I get pyarrow objects into and back from Redis.

参考:如何设置/从Redis获取pandas.DataFrame?

推荐答案

这是一个使用 pyarrow 序列化 Pandas 数据帧以存储在 redis 中的完整示例

Here's a full example to use pyarrow for serialization of a pandas dataframe to store in redis

apt-get install python3 python3-pip redis-server
pip3 install pandas pyarrow redis

然后在python中

import pandas as pd
import pyarrow as pa
import redis

df=pd.DataFrame({'A':[1,2,3]})
r = redis.Redis(host='localhost', port=6379, db=0)

context = pa.default_serialization_context()
r.set("key", context.serialize(df).to_buffer().to_pybytes())
context.deserialize(r.get("key"))
   A
0  1
1  2
2  3

我刚刚向 pandas 提交了 PR 28494 以将这个 pyarrow 示例包含在文档.

I just submitted PR 28494 to pandas to include this pyarrow example in the docs.

参考文档:

• https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_msgpack.html
• https://arrow.apache.org/docs/python/ipc.html#arbitrary-object-serialization
• https://arrow.apache.org/docs/python/memory.html#pyarrow-buffer
• https://stackoverflow.com/a/37957490/4126114

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