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Build Pipelines with Live BigQuery Data in Google Cloud Data Fusion (via CData Connect Cloud)
Use CData Connect Cloud to connect to BigQuery from Google Cloud Data Fusion, enabling the integration of live BigQuery data into the building and management of effective data pipelines.
Google Cloud Data Fusion simplifies building and managing data pipelines by offering a visual interface to connect, transform, and move data across various sources and destinations, streamlining data integration processes. When combined with CData Connect Cloud, it provides access to BigQuery data for building and managing ELT/ETL data pipelines. This article explains how to use CData Connect Cloud to create a live connection to BigQuery and how to connect and access live BigQuery data from the Cloud Data Fusion platform.
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
Configure BigQuery Connectivity for Cloud Data Fusion
Connectivity to BigQuery from Cloud Data Fusion is made possible through CData Connect Cloud. To work with BigQuery data from Cloud Data Fusion, we start by creating and configuring a BigQuery connection.
- Log into Connect Cloud, click Connections and click Add Connection
![]( "Adding a Connection")
- Select "BigQuery" from the Add Connection panel
![]( "Selecting a data source")
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BigQuery uses OAuth to authenticate. Click "Sign in" to authenticate with BigQuery.
![]( "Authenticating with OAuth (Salesforce is shown).")
- Navigate to the Permissions tab in the Add BigQuery Connection page and update the User-based permissions.
![]( "Updating permissions")
Add a Personal Access Token
If you are connecting from a service, application, platform, or framework that does not support OAuth authentication, you can create a Personal Access Token (PAT) to use for authentication. Best practices would dictate that you create a separate PAT for each service, to maintain granularity of access.
- Click on your username at the top right of the Connect Cloud app and click User Profile.
- On the User Profile page, scroll down to the Personal Access Tokens section and click Create PAT.
- Give your PAT a name and click Create.
- The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.
With the connection configured, you are ready to connect to BigQuery data from Cloud Data Fusion.
Connecting to BigQuery from Cloud Data Fusion
Follow these steps to establish a connection from Cloud Data Fusion to BigQuery through the CData Connect Cloud JDBC driver:
- Download and install the CData Connect Cloud JDBC driver:
- Open the Client Tools page of CData Connect Cloud.
- Search for JDBC or Cloud Data Fusion.
- Click on Download and select your operating system (Mac/Windows/Linux).
- Once the download is complete, run the setup file.
- When the installation is complete, the JAR file can be found in the installation directory (inside the lib folder).
- Log into Cloud Data Fusion.
- Click the green "+" button at the top right to add an entity.
- Under Driver, click Upload.
![]( "Upload the driver JAR file")
- Now, upload the CData Connect Cloud JDBC driver (JAR file).
- Enter the driver settings:
- Name: Enter the name of the driver
- Class name: Enter "cdata.jdbc.connect.ConnectDriver"
- Version: Enter the driver version
- Description (optional): Enter a description for the driver
![]( "Enter the driver settings")
- Click on Finish.
- Enter source configuration settings:
- Label: Helps to identify the connection
- JDBC driver name: Enter the JDBC driver name to identify the driver configured in Step 6.
- Connection string: Enter the JDBC connection string and include the following parameters in it:
jdbc:connect:AuthScheme=Basic;User=[User];Password=[Password]; - User: Enter your CData Connect Cloud username, displayed in the top-right corner of the CData Connect Cloud interface. For example, "test@cdata.com"
- Password: Enter the PAT you generated on the Settings page.
![]( "Enter the source configuration settings")
- Click Validate in the top right corner.
- If the connection is successful, you can manage the pipeline by editing it through the UI.
![]( "Build and manage the pipeline in the UI")
- Run the pipepline created.
![]( "Run the pipeline")
Troubleshooting
Please be aware that there is a known issue in Cloud Data Fusion where "int" types from source data are automatically cast as "long".
Live Access to BigQuery Data from Cloud Applications
Now you have a direct connection to live BigQuery data from from Google Cloud Data Fusion. You can create more connections to ensure a smooth movement of data across various sources and destinations, thereby streamlining data integration processes - all without replicating BigQuery data.
To get real-time data access to 100+ SaaS, Big Data, and NoSQL sources (including BigQuery) directly from your cloud applications, explore the CData Connect Cloud.
