连接池新手 [英] New to Connection Pooling

问题描述

所以我是连接池的新手.我试图确定如何使用池以加快查询速度.我有一个有效的查询，但我认为我使用的池不正确.这是语法，如果您发现我可以提高效率的任何地方，请告诉我.

So I am new to connection pooling. I am trying to determine how to use a pool in order to speed up my query. I have a query that works, but I dont think I am using the pool correct. Here is the syntax, if you see anywhere I could be more efficient please let me know.

try:
    db=mysql.connector.connect(poolname="mypool", pool_size=10, **config)
    
    cursor.execute(query1)
    df1=create_df(cursor)
    
    cursor.execute(query2)
    df2=create_df(cursor)
    
    cursor.execute(query3)
    df3=create_df(cursor)
    

推荐答案

您的问题不清楚， cursor 是如何从 db 来的.

Your question didn't make it clear how cursor comes from db.

考虑使用 sqlalchemy .然后，您将免费获得自动池化.

Consider using sqlalchemy. Then you get automatic pooling for free.

import pandas as pd
import sqlalchemy as sa

engine = sa.create_engine(your_local_mysql_url_with_credentials)
with engine.connect() as con:
    df1 = pd.read_sql(query1, con)
    df2 = pd.read_sql(query2, con)
    df3 = pd.read_sql(query3, con)

该池最终成为 engine 的属性.实际上，您很少关心检查它，既然可以正常工作，就可以跨查询挂接到服务器的TCP连接上.

The pool winds up being an attribute of engine. In practice you'll seldom care about inspecting it, since it Just Works, hanging onto a server TCP connection across queries.

这篇关于连接池新手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！