Connect to BigQuery Data in HULFT Integrate

HULFT Integrate is a modern data integration platform that provides a drag-and-drop user interface to create cooperation flows, data conversion, and processing so that complex data connections are easier than ever to execute. When paired with the CData JDBC Driver for Google BigQuery, HULFT Integrate can work with live BigQuery data. This article explains how to connect to BigQuery and move the data into a CSV file.

With built-in optimized data processing, the CData JDBC driver offers unmatched performance for interacting with live BigQuery data. When you issue complex SQL queries to BigQuery, the driver pushes supported SQL operations, like filters and aggregations, directly to BigQuery and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations). Its built-in dynamic metadata querying allows you to work with and analyze BigQuery data using native data types.

Getting Started

---

Enable Access to BigQuery

To enable access to BigQuery data from HULFT Integrate projects:

1. Copy the CData JDBC Driver JAR file (and license file if it exists), cdata.jdbc.googlebigquery.jar (and cdata.jdbc.googlebigquery.lic), to the jdbc_adapter subfolder for the Integrate Server
2. Restart the HULFT Integrate Server and launch HULFT Integrate Studio

Build a Project with Access to BigQuery Data

Once you copy the JAR files, you can create a project with access to BigQuery data. Start by opening Integrate Studio and creating a new project.

1. Name the project
2. Ensure the "Create script" checkbox is checked
3. Click Next 👁 Creating a new project.
   
4. Name the script (e.g.: GoogleBigQuerytoCSV)

Once you create the project, add components to the script to copy BigQuery data to a CSV file.

Configure an Execute Select SQL Component

Drag an "Execute Select SQL" component from the Tool Palette (Database -> JDBC) into the Script workspace.

1. In the "Required settings" tab for the Destination, click "Add" to create a new connection for BigQuery. Set the following properties:
   • Name: BigQuery Connection Settings
   • Driver class name: cdata.jdbc.googlebigquery.GoogleBigQueryDriver
   • URL: jdbc:googlebigquery:DataSetId=MyDataSetId;ProjectId=MyProjectId;InitiateOAuth=GETANDREFRESH;
     
     👁 JDBC connection settings (Salesforce is shown).
     

     Built-in Connection String Designer

     For assistance 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.

     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, register an application to obtain the OAuth JWT values.

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

     👁 Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)
     
2. Write your SQL statement. For example:

   SELECT OrderName, Freight FROM Orders

3. Click "Extraction test" to ensure the connection and query are configured properly
4. Click "Execute SQL statement and set output schema"
5. Click "Finish" 👁 Configuring the Execute Select SQL operation
   

Configure a Write CSV File Component

Drag a "Write CSV File" component from the Tool Palette (File -> CSV) onto the workspace.

1. Set a file to write the query results to (e.g. Orders.csv)
2. Set "Input data" to the "Select SQL" component
3. Add columns for each field selected in the SQL query
4. In the "Write settings" tab, check the checkbox to "Insert column names into first row"
5. Click "Finish"

Map BigQuery Fields to the CSV Columns

Map each column from the "Select" component to the corresponding column for the "CSV" component.

Finish the Script

Drag the "Start" component onto the "Select" component and the "CSV" component onto the "End" component. Build the script and run the script to move BigQuery data into a CSV file.

👁 A completed script.

Download a free, 30-day trial of the CData JDBC Driver for Google BigQuery and start working with your live BigQuery data in HULFT Integrate. Reach out to our Support Team if you have any questions.