PyCharm でCData ODBC Driver for Hive を使ってみた

CData ODBC Drivers は、ODBC をサポートするあらゆる環境から利用可能です。 本記事では、PyCharm からのCData ODBC Driver for Hive の利用を説明します。ODBC Deriver をデータソースとして設定する方法、データソースをクエリするPyCharm のベーシックな方法を含みます。

To begin, this tutorial will assume that you have already installed the CData ODBC Driver for Hive as well as PyCharm.

Pyodbc をプロジェクトに追加

Follow the steps below to add the pyodbc module to your project.

1. Click File -> Settings to open the project settings window.
2. Click Project Interpreter from the Project: YourProjectName menu.
3. To add pyodbc, click the + button and enter pyodbc.
4. Click Install Package to install pyodbc.

Hive への接続

You can now connect with an ODBC connection string or a DSN. See the Getting Started section in the CData driver documentation for a guide to creating a DSN on your OS.

Set the Server, Port, TransportMode, and AuthScheme connection properties to connect to Hive.

Below is the syntax for a DSN:

[CData ApacheHive Source] Driver = CData ODBC Driver for Hive Description = My Description Server = 127.0.0.1 Port = 10000 TransportMode = BINARY

Hive へのクエリの実行

Instantiate a Cursor and use the execute method of the Cursor class to execute any SQL statement.

import pyodbc cnxn = pyodbc.connect('DRIVER={CData ODBC Driver for ApacheHive};Server = 127.0.0.1;Port = 10000;TransportMode = BINARY;') cursor = cnxn.cursor() cursor.execute("SELECT City, CompanyName FROM Customers WHERE Country = 'US'") rows = cursor.fetchall() for row in rows: print(row.City, row.CompanyName)

After connecting to Hive in PyCharm using the CData ODBC Driver, you will be able to build Python apps with access to Hive data as if it were a standard database. If you have any questions, comments, or feedback regarding this tutorial, please contact us at support@cdata.com.