我在Windows 7上安装了python 2.7.0和Teradata模块。我无法从python连接和quyey TD。
pip install Teradata
现在我想使用Python导入teradata模块并执行类似 -
的操作请帮我编写代码,因为我是Python的新手,并且我没有任何信息可以连接到teradata。
答案 0 :(得分:16)
有很多方法可以连接到Teradata并将表导出到Pandas。这是三个:
# You can install teradata via PIP: pip install teradata
# to get a list of your odbc drivers names, you could do: teradata.tdodbc.drivers
import teradata
import pandas as pd
host,username,password = 'HOST','UID', 'PWD'
#Make a connection
udaExec = teradata.UdaExec (appName="test", version="1.0", logConsole=False)
with udaExec.connect(method="odbc",system=host, username=username,
password=password, driver="DRIVERNAME") as connect:
query = "SELECT * FROM DATABASEX.TABLENAMEX;"
#Reading query to df
df = pd.read_sql(query,connect)
# do something with df,e.g.
print(df.head()) #to see the first 5 rows
import pyodbc
#You can install teradata via PIP: pip install pyodbc
#to get a list of your odbc drivers names, you could do: pyodbc.drivers()
#Make a connection
link = 'DRIVER={DRIVERNAME};DBCNAME={hostname};UID={uid};PWD={pwd}'.format(
DRIVERNAME=DRIVERNAME,hostname=hostname,
uid=username, pwd=password)
with pyodbc.connect(link,autocommit=True) as connect:
#Reading query to df
df = pd.read_sql(query,connect)
#You can install sqlalchemy via PIP: pip install sqlalchemy-teradata
#Note: It is not pip install sqlalchemy. If you already have sqlalchemy, you still need sqlalchemy-teradata to get teradata dialects
from sqlalchemy import create_engine
#Make a connection
link = 'teradata://{username}:{password}@{hostname}/?driver={DRIVERNAME}'.format(
username=username,hostname=hostname,DRIVERNAME=DRIVERNAME)
with create_engine(link) as connect:
#Reading query to df
df = pd.read_sql(query,connect)
使用giraffez module还有第四种方法。我喜欢使用这个模块,因为它附带了MLOAD,FASTLOAD,BULKEXPORT等。初学者的唯一问题是它的要求(例如C / C ++编译器,Teradata CLIv2和TPT API头文件/ lib文件)。
注意:更新了13-07-2018,使用上下文管理器确保会话结束
更新:31-10-2018:使用teradata将数据从df发送到teradata
我们可以将数据从df发送到Teradata。避免' odbc' 1 MB限制以及odbc驱动程序依赖,我们可以使用' rest'方法。我们需要主机ip_address,而不是驱动程序参数。 NB: df中列的顺序应与Teradata表中的列顺序相匹配。
import teradata
import pandas as pd
# HOST_IP can be found by executing *>>nslookup viewpoint* or *ping viewpoint*
udaExec = teradata.UdaExec (appName="test", version="1.0", logConsole=False)
with udaExec.connect(method="rest",system="DBName", username="UserName",
password="Password", host="HOST_IP_ADDRESS") as connect:
data = [tuple(x) for x in df.to_records(index=False)]
connect.executemany("INSERT INTO DATABASE.TABLEWITH5COL")
values(?,?,?,?,?)",data,batch=True)
使用' odbc',您必须将数据块化为少于1MB的块以避免" [HY001] [Teradata] [ODBC Teradata Driver]内存分配错误"错误:例如。
import teradata
import pandas as pd
import numpy as np
udaExec = teradata.UdaExec (appName="test", version="1.0", logConsole=False)
with udaExec.connect(method="odbc",system="DBName", username="UserName",
password="Password", driver="DriverName") as connect:
#We can divide our huge_df to small chuncks. E.g. 100 churchs
chunks_df = np.array_split(huge_df, 100)
#Import chuncks to Teradata
for i,_ in enumerate(chunks_df):
data = [tuple(x) for x in chuncks_df[i].to_records(index=False)]
connect.executemany("INSERT INTO DATABASE.TABLEWITH5COL values(?,?,?,?,?)",data,batch=True)
答案 1 :(得分:4)
从互联网下载Teradata Python模块和python pyodbc.pyd。 使用cmd install setup.py安装。
以下是连接teradata和提取数据的示例脚本:
import teradata
import pyodbc
import sys
udaExec = teradata.UdaExec (appName="HelloWorld", version="1.0",
logConsole=False)
session = udaExec.connect(method="odbc", dsn="prod32",
username="PRODRUN", password="PRODRUN");
i = 0
REJECTED = 'R';
f = file("output.txt","w");sys.stdout=f
cursor = session.cursor();
ff_remaining = 0;
cnt = cursor.execute("SELECT SEQ_NO,FRQFBKDC,PNR_RELOC FROM ttemp.ffremaining ORDER BY 1,2,3 ").rowcount;
rows = cursor.execute("SELECT SEQ_NO,FRQFBKDC,PNR_RELOC FROM ttemp.ffremaining ORDER BY 1,2,3 ").fetchall();
for i in range(cnt):
ff_remaining = cursor.execute("select count(*) as coun from ttemp.ffretroq_paxoff where seq_no=? and status <> ?",(rows[i].seq_no,REJECTED)).fetchall();
print ff_remaining[0].coun, rows[i].seq_no, REJECTED;
答案 2 :(得分:3)
要添加到Prayson's答案中,可以使用teradatasql程序包(found on pypi)。该软件包不需要您安装Teradata驱动程序(此软件包除外)。像这样使用它:
import teradatasql
import pandas as pd
with teradatasql.connect(host='host', user='username', password='password') as connect:
data = pd.read_sql('select top 5 * from table_name;', connect)