如何使用 pyarrow set/get Pandas 数据帧到 Redis

Question

使用

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

Pre Pandas 0.25，以下有效。

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..

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 对象传入和传出 Redis。

参考：

Answer 1

这是一个完整的示例，使用 pyarrow 序列化 pandas 数据帧以存储在 redis

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

然后在 python

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

我刚刚将 PR 28494 提交给 pandas 以将此 pyarrow 示例包含在文档中。

参考文档：

Answer 2

这是我的做法，因为 default_serialization_context 已被弃用，事情也更简单了：

import pyarrow as pa
import redis

pool = redis.ConnectionPool(host='localhost', port=6379, db=0)
r = redis.Redis(connection_pool=pool)

def storeInRedis(alias, df):
    df_compressed = pa.serialize(df).to_buffer().to_pybytes()
    res = r.set(alias,df_compressed)
    if res == True:
        print(f'{alias} cached')

def loadFromRedis(alias):
    data = r.get(alias)
    try:
        return pa.deserialize(data)
    except:
        print("No data")


storeInRedis('locations', locdf)

loadFromRedis('locations')

Answer 3

如果您想压缩 Redis 中的数据，可以使用对 parquet 和 gzip 的内置支持

def openRedisCon():
   pool = redis.ConnectionPool(host=REDIS_HOST, port=REDIS_PORT, db=0)
   r = redis.Redis(connection_pool=pool)
   return r

def storeDFInRedis(alias, df):
    """Store the dataframe object in Redis
    """

    buffer = io.BytesIO()
    df.to_parquet(buffer, compression='gzip')
    buffer.seek(0) # re-set the pointer to the beginning after reading
    r = openRedisCon()
    res = r.set(alias,buffer.read())

def loadDFFromRedis(alias, useStale: bool = False):
    """Load the named key from Redis into a DataFrame and return the DF object
    """

    r = openRedisCon()

    try:
        buffer = io.BytesIO(r.get(alias))
        buffer.seek(0)
        df = pd.read_parquet(buffer)
        return df
    except:
        return None

Answer 4

Pickle 和 zlib 可以替代 pyarrow：

import pandas as pd
import redis
import zlib
import pickle

df=pd.DataFrame({'A':[1,2,3]})
r = redis.Redis(host='localhost', port=6379, db=0)
r.set("key", zlib.compress( pickle.dumps(df)))
df=pickle.loads(zlib.decompress(r.get("key")))

如何使用 pyarrow set/get Pandas 数据帧到 Redis

How to set/get Pandas dataframes into Redis using pyarrow

python

redis

pandas

pyarrow

py-redis