Python将Cassandra数据读入 pandas [英] Python read Cassandra data into pandas

问题描述

将Cassandra数据读入熊猫的正确且最快的方法是什么?现在，我使用以下代码，但是它非常慢...

What is the proper and fastest way to read Cassandra data into pandas? Now I use the following code but it's very slow...

import pandas as pd

from cassandra.cluster import Cluster
from cassandra.auth import PlainTextAuthProvider
from cassandra.query import dict_factory

auth_provider = PlainTextAuthProvider(username=CASSANDRA_USER, password=CASSANDRA_PASS)
cluster = Cluster(contact_points=[CASSANDRA_HOST], port=CASSANDRA_PORT,
    auth_provider=auth_provider)

session = cluster.connect(CASSANDRA_DB)
session.row_factory = dict_factory

sql_query = "SELECT * FROM {}.{};".format(CASSANDRA_DB, CASSANDRA_TABLE)

df = pd.DataFrame()

for row in session.execute(sql_query):
    df = df.append(pd.DataFrame(row, index=[0]))

df = df.reset_index(drop=True).fillna(pd.np.nan)

读取1000行需要1分钟，而我还有一个更多"的地方... 如果我运行相同的查询，例如.在DBeaver中，我在一分钟内就能得到全部结果(约4万行).

Reading 1000 rows takes 1 minute, and I have a "bit more"... If I run the same query eg. in DBeaver, I get the whole results (~40k rows) within a minute.

谢谢！

推荐答案

我在官方

I got the answer at the official mailing list (it works perfectly):

尝试定义自己的熊猫行工厂:

try to define your own pandas row factory:

def pandas_factory(colnames, rows):
    return pd.DataFrame(rows, columns=colnames)

session.row_factory = pandas_factory
session.default_fetch_size = None

query = "SELECT ..."
rslt = session.execute(query, timeout=None)
df = rslt._current_rows

这就是我这样做的方式-它应该更快...

That's the way i do it - an it should be faster...

如果您找到更快的方法-我对:)

If you find a faster method - i'm interested in :)

迈克尔

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