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Get the Report →Using the CData ODBC Driver for Impala in PyCharm
Connect to Impala as an ODBC data source in PyCharm using the CData ODBC Driver for Impala.
The CData ODBC Drivers can be used in any environment that supports loading an ODBC Driver. In this tutorial we will explore using the CData ODBC Driver for Impala from within PyCharm. Included are steps for adding the CData ODBC Driver as a data source, as well as basic PyCharm code to query the data source and display results.
To begin, this tutorial will assume that you have already installed the CData ODBC Driver for Impala as well as PyCharm.
Add Pyodbc to the Project
Follow the steps below to add the pyodbc module to your project.
- Click File -> Settings to open the project settings window.
- Click Project Interpreter from the Project: YourProjectName menu.
- To add pyodbc, click the + button and enter pyodbc.
- Click Install Package to install pyodbc.
Connect to Impala
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.
In order to connect to Apache Impala, set the Server, Port, and ProtocolVersion. You may optionally specify a default Database. To connect using alternative methods, such as NOSASL, LDAP, or Kerberos, refer to the online Help documentation.
Below is the syntax for a DSN:
[CData ApacheImpala Source]
Driver = CData ODBC Driver for Impala
Description = My Description
Server = 127.0.0.1
Port = 21050
Execute SQL to Impala
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 ApacheImpala};Server = 127.0.0.1;Port = 21050;')
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 Impala in PyCharm using the CData ODBC Driver, you will be able to build Python apps with access to Impala data as if it were a standard database. If you have any questions, comments, or feedback regarding this tutorial, please contact us at [email protected].