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 Pandas 的正确和最快方法是什么?现在我使用下面的代码但是它很慢...
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)
阅读 1000 行需要 1 分钟,而我还有多一点"...如果我运行相同的查询,例如.在 DBeaver 中,我在一分钟内获得了全部结果(约 40k 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
我在官方邮件列表(完美运行):
I got the answer at the official mailing list (it works perfectly):
尝试定义自己的pandas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
这就是我做的方式 - 它应该更快......
That's the way i do it - an it should be faster...
如果你找到一个更快的方法 - 我很感兴趣 :)
If you find a faster method - i'm interested in :)
迈克尔
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