Python 读取千万级数据自动写入 MySQL 数据库

import pandas as pd
data = pd.read_csv('./tianchi_mobile_recommend_train_user.csv')
data.shape

运行结果（csv 格式 ，大约 1200万行）：

（12256906，6）

import pymysql

# 数据库连接信息
conn = pymysql.connect(
       host='127.0.0.1',
       user='root',
       passwd='wws666',
       db='mobile', 
       port = 3306,
       charset="utf8")

# 分块处理
big_size = 100000
# 分块遍历写入到 mysql    
with pd.read_csv('./tianchi_mobile_recommend_train_user.csv',chunksize=big_size) as reader:
    for df in reader:
        datas = []
        print('处理：',len(df))
		#print(df)
        for i ,raw in df.iterrows():
            data = (raw['user_id'],raw['item_id'],raw['behavior_type'],
                    raw['item_category'],raw['time'])
            datas.append(data)
        _values = ",".join(['%s', ] * 5) #'%s,%s,%s,%s,%s'
        sql = """insert into users(user_id,item_id,behavior_type
        ,item_category,time) values(%s)""" % _values
        cursor = conn.cursor()
        cursor.executemany(sql,datas)
        conn.commit()
 # 关闭服务      
conn.close()
cursor.close()
print('存入成功！')

from sqlalchemy import create_engine
engine = create_engine('mysql+pymysql://root:wws666@localhost:3306/mobile')
data = pd.read_csv('./tianchi_mobile_recommend_train_user.csv')
data.to_sql('user02',engine,chunksize=100000,index=None)
print('存入成功！')