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Use JayDeBeApi to access BigQuery Data in Python
Use standard Python scripting and the development environment of your choice to access live BigQuery data.
Access BigQuery data with Python scripts and standard SQL on any machine where Python and Java can be installed. You can use the CData JDBC Driver for Google BigQuery and the JayDeBeApi module to work with remote BigQuery data in Python. By using the CData Driver, you are leveraging a driver written for industry-proven standards to access your data in the popular Python language. This article shows how to use the driver to execute SQL queries to BigQuery and visualize BigQuery data with standard Python.
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
Use the JayDeBeApi module
JayDeBeApi is a Python library that serves as a JDBC (Java Database Connectivity) bridge, allowing Python programs to interact with Java databases, including CData JDBC Drivers. Use the pip install command to install the module:
pip install JayDeBeApi
Create the JDBC URL
Once you have JayDeBeApi installed, you are ready to work with BigQuery data in Python using SQL.
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.
Built-in Connection String Designer
For assistance in constructing the JDBC URL, use the connection string designer built into the BigQuery JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.
java -jar cdata.jdbc.googlebigquery.jar
Fill in the connection properties and copy the connection string to the clipboard.
Below is a sample variable assignment, including a typical JDBC connection string:
jdbc_url = "jdbc:googlebigquery:DataSetId=MyDataSetId;ProjectId=MyProjectId;InitiateOAuth=GETANDREFRESH"
Access BigQuery data in Python
With the JDBC URL configured, you only need the absolute path to the JDBC driver JAR file, which is in the "lib" folder in the installation directory ("C:\Program Files\CData[product_name] 20XX\lib\cdata.jdbc.googlebigquery.jar" on Windows).
NOTE: If you haven't already, set the JAVA_HOME environment variable to the Java installation directory.
Use code similar to the follow to read and print data from BigQuery:
import jaydebeapi
#The JDBC connection string
jdbc_url = "jdbc:googlebigquery:DataSetId=MyDataSetId;ProjectId=MyProjectId;InitiateOAuth=GETANDREFRESH"
username = "****"
password = "****"
#The absolute Path to the JDBC driver JAR file, typically:
jdbc_driver_jar = "C:\Program Files\CData[product_name] 20XX\lib\cdata.jdbc.googlebigquery.jar"
conn = jaydebeapi.connect(
"cdata.jdbc.googlebigquery.GoogleBigQueryDriver",
jdbc_url,
[username, password],
jdbc_driver_jar,
)
cursor = conn.cursor()
cursor.execute("SELECT * FROM Orders;")
results = cursor.fetchall()
for row in results:
print(row)
cursor.close()
conn.close()
Free trial & more information
Download a free, 30-day trial of the CData JDBC Driver for Google BigQuery and start working with your live BigQuery data in Python. Reach out to our Support Team if you have any questions.
Ready to get started?
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Google BigQuery JDBC Driver
Rapidly create and deploy powerful Java applications that integrate with Google BigQuery data including Tables and Datasets.
