How to Connect to Google BigQuery using SSIS
Big data processing is essential, but managing it shouldn't be overcomplicated. Google BigQuery excels at handling massive datasets in the cloud, while SSIS is a go-to option for ETL workflows. However, connecting these two platforms can be challenging. That's where Devart SSIS Components for BigQuery step in.
Designed specifically for BigQuery data access, these components transform integration workflows into efficient and effortless operations, addressing the most common pain points for developers, engineers, DBAs, and other data professionals.
Create data flow tasks for BigQuery
Before we commence working with SSIS and BigQuery using Devart SSIS Data Flow Components, make sure the following prerequisites are in place:
- SQL Server Data Tools (SSDT) for Visual Studio and SSIS for Visual Studio must be installed
- The Devart SSIS Data Flow Components for BigQuery must be installed
- The system must match the compatibility requirements
Setting up the Data Flow Task for BigQuery is straightforward:
- 1. Launch Visual Studio, open the necessary SSIS project and navigate to the Control Flow tab.
- 2. Right-click and select New Data Flow Task. Rename it, for instance, to BigQuery Data Import.
- 3. Double-click the task to access the Data Flow tab.
Configure a SSIS BigQuery connection
To connect SSIS to BigQuery with Devart SSIS Components, do the following:
Right-click the Connection Managers panel and select New Connection. Choose Google BigQuery from the available connection types.
Configure the following settings in the Connection Manager Editor:
- Refresh Token - the OAuth token for authentication
- Project ID - the Google Cloud Project identifier
- Dataset ID - the BigQuery dataset name
Click Test Connection to verify the details.
Select BigQuery data for retrieving using SSIS
First, you need to add a Source Component to the Data Flow Task.
In the Devart BigQuery Source Editor, select the BigQuery connection you configured.
You will see the list of available tables to choose from on the left. Choose the table and specify the SQL query to retrieve the data from the table.
You don't need to construct the SELECT query manually, simply drag and drop the desired table into the Query field, and the query will be generated automatically. After that, you can preview the data.
You can write and use custom queries for more targeted and precise results. The Source Editor provides the necessary functionality that allows you to write and execute complex SQL queries against the BigQuery data source. Additionally, you can save queries as templates to reuse in future for similar tasks.