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How to Connect to BigQuery Data in Using Python: 6 Steps


Create Python applications on Linux/UNIX machines with connectivity to BigQuery data. Leverage the pyodbc module for ODBC in Python.

The rich ecosystem of Python modules lets you get to work quicker and integrate your systems more effectively. With the CData Linux/UNIX ODBC Driver for BigQuery and the pyodbc module, you can easily build BigQuery-connected Python applications. This article shows how to use the pyodbc built-in functions to connect to BigQuery data, execute queries, and output the results.

How to Use the CData ODBC Drivers on UNIX/Linux

The CData ODBC Drivers are supported in various Red Hat-based and Debian-based systems, including Ubuntu, Debian, RHEL, CentOS, and Fedora. There are also several libraries and packages that are required, many of which may be installed by default, depending on your system. For more information on the supported versions of Linux operating systems and the required libraries, please refer to the "Getting Started" section in the help documentation (installed and found online).

About BigQuery Data Integration

CData simplifies access and integration of live Google BigQuery data. Our customers leverage CData connectivity to:

  • Simplify access to BigQuery with broad out-of-the-box support for authentication schemes, including OAuth, OAuth JWT, and GCP Instance.
  • Enhance data workflows with Bi-directional data access between BigQuery and other applications.
  • Perform key BigQuery actions like starting, retrieving, and canceling jobs; deleting tables; or insert job loads through SQL stored procedures.

Most CData customers are using Google BigQuery as their data warehouse and so use CData solutions to migrate business data from separate sources into BigQuery for comprehensive analytics. Other customers use our connectivity to analyze and report on their Google BigQuery data, with many customers using both solutions.

For more details on how CData enhances your Google BigQuery experience, check out our blog post: https://www.cdata.com/blog/what-is-bigquery


Getting Started


1. Install the Driver Manager

Before installing the driver, check that your system has a driver manager. For this article, you will use unixODBC, a free and open source ODBC driver manager that is widely supported.

For Debian-based systems like Ubuntu, you can install unixODBC with the APT package manager:

$ sudo apt-get install unixodbc unixodbc-dev

For systems based on Red Hat Linux, you can install unixODBC with yum or dnf:

$ sudo yum install unixODBC unixODBC-devel

The unixODBC driver manager reads information about drivers from an odbcinst.ini file and about data sources from an odbc.ini file. You can determine the location of the configuration files on your system by entering the following command into a terminal:

$ odbcinst -j

The output of the command will display the locations of the configuration files for ODBC data sources and registered ODBC drivers. User data sources can only be accessed by the user account whose home folder the odbc.ini is located in. System data sources can be accessed by all users. Below is an example of the output of this command:

DRIVERS............: /etc/odbcinst.ini SYSTEM DATA SOURCES: /etc/odbc.ini FILE DATA SOURCES..: /etc/ODBCDataSources USER DATA SOURCES..: /home/myuser/.odbc.ini SQLULEN Size.......: 8 SQLLEN Size........: 8 SQLSETPOSIROW Size.: 8

2. Install the Driver

You can download the driver in standard package formats: the Debian .deb package format or the .rpm file format. Once you have downloaded the file, you can install the driver from the terminal.

The driver installer registers the driver with unixODBC and creates a system DSN, which can be used later in any tools or applications that support ODBC connectivity.

For Debian-based systems like Ubuntu, run the following command with sudo or as root: $ dpkg -i /path/to/package.deb

For Red Hat systems and other systems that support .rpms, run the following command with sudo or as root: $ rpm -i /path/to/package.rpm

Once the driver is installed, you can list the registered drivers and defined data sources using the unixODBC driver manager:

List the Registered Driver(s)

$ odbcinst -q -d CData ODBC Driver for Google BigQuery ...

List the Defined Data Source(s)

$ odbcinst -q -s CData GoogleBigQuery Source ...

To use the CData ODBC Driver for Google BigQuery with unixODBC, ensure that the driver is configured to use UTF-16. To do so, edit the INI file for the driver (cdata.odbc.googlebigquery.ini), which can be found in the lib folder in the installation location (typically /opt/cdata/cdata-odbc-driver-for-googlebigquery), as follows:

cdata.odbc.googlebigquery.ini

... [Driver] DriverManagerEncoding = UTF-16

3. Modify the DSN

The driver installation predefines a system DSN. You can modify the DSN by editing the system data sources file (/etc/odbc.ini) and defining the required connection properties. Additionally, you can create user-specific DSNs that will not require root access to modify in $HOME/.odbc.ini.

Google uses the OAuth authentication standard. To access Google APIs on behalf of individual users, you can use the embedded credentials or you can register your own OAuth app.

OAuth also enables you to use a service account to connect on behalf of users in a Google Apps domain. To authenticate with a service account, you will need to register an application to obtain the OAuth JWT values.

In addition to the OAuth values, you will need to specify the DatasetId and ProjectId. See the "Getting Started" chapter of the help documentation for a guide to using OAuth.

/etc/odbc.ini or $HOME/.odbc.ini

[CData GoogleBigQuery Source] Driver = CData ODBC Driver for Google BigQuery Description = My Description DataSetId = MyDataSetId ProjectId = MyProjectId

For specific information on using these configuration files, please refer to the help documentation (installed and found online).

You can follow the procedure below to install pyodbc and start accessing BigQuery through Python objects.

4. Install pyodbc

You can use the pip utility to install the module:

pip install pyodbc

Be sure to import with the module with the following:

import pyodbc

5. Connect to BigQuery Data

You can now connect with an ODBC connection string or a DSN. Below is the syntax for a connection string:

cnxn = pyodbc.connect('DRIVER={CData ODBC Driver for Google BigQuery};DataSetId=MyDataSetId;ProjectId=MyProjectId;')

Below is the syntax for a DSN:

cnxn = pyodbc.connect('DSN=CData GoogleBigQuery Sys;')

6. Execute SQL on BigQuery

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

cursor = cnxn.cursor()

Select

You can use fetchall, fetchone, and fetchmany to retrieve Rows returned from SELECT statements:

import pyodbc cursor = cnxn.cursor() cnxn = pyodbc.connect('DSN=CData GoogleBigQuery Source;User=MyUser;Password=MyPassword') cursor.execute("SELECT OrderName, Freight FROM Orders WHERE ShipCity = 'New York'") rows = cursor.fetchall() for row in rows: print(row.OrderName, row.Freight)

You can provide parameterized queries in a sequence or in the argument list:

cursor.execute( "SELECT OrderName, Freight FROM Orders WHERE ShipCity = ?", 'New York',1)

Insert

INSERT commands also use the execute method; however, you must subsequently call the commit method after an insert or you will lose your changes:

cursor.execute("INSERT INTO Orders (ShipCity) VALUES ('New York')") cnxn.commit()

Update and Delete

As with an insert, you must also call commit after calling execute for an update or delete:

cursor.execute("UPDATE Orders SET ShipCity = 'New York'") cnxn.commit()

Metadata Discovery

You can use the getinfo method to retrieve data such as information about the data source and the capabilities of the driver. The getinfo method passes through input to the ODBC SQLGetInfo method.

cnxn.getinfo(pyodbc.SQL_DATA_SOURCE_NAME)

You are now ready to build Python apps in Linux/UNIX environments with connectivity to BigQuery data, using the CData ODBC Driver for Google BigQuery.

Ready to get started?

Download a free trial of the Google BigQuery ODBC Driver to get started:

 Download Now

Learn more:

Google BigQuery Icon Google BigQuery ODBC Driver

The Google BigQuery ODBC Driver is a powerful tool that allows you to connect with live Google BigQuery data, directly from any applications that support ODBC connectivity.

Access Google BigQuery like you would a database - read, write, and update Datasets, Tables, etc. through a standard ODBC Driver interface.

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