The BigQuery extractor loads data from BigQuery and brings it into Keboola Connection. Running the extractor creates a background job that
Note: Using the Google BigQuery extractor is also described in our Getting Started Tutorial.
To access and extract data from your BigQuery dataset, you need to set up a Google Service Account. Go
to Google Cloud Platform Console > IAM & admin > Service accounts
and select the project you want the extractor to have access to. Click Create Service Account
and enter a Service account name (e.g.,
Keboola Connection BigQuery Extractor).
Then add the
BigQuery Data Editor,
BigQuery Job User and
Storage Object Admin roles.
Finally, create a new JSON key (click + Create key) and download it to your computer (click Create).
The extractor uses Google Storage Bucket as a temporary storage for off-loading the data from BigQuery. Go to the Google Cloud Platform Console > Storage > Browser and click Create Bucket. Enter the Name of your bucket and select its Location (must be the same as of your dataset).
Do not set a Retention Policy on the bucket. The bucket contains only temporary data and no retention is needed.
Create a new configuration of the BigQuery extractor. Click the Set Service Account Key button.
Click on the Save button to store the credentials. Important: The private key is stored in an encrypted form and only the non-sensitive parts are visible in the UI for your verification. The key can be deleted or replaced by a new one at any time.
In the Unload Configuration section, fill Cloud Storage Bucket Name as the name of the bucket you have created earlier, and select the correct Dataset Location. Click Save.
Start by clicking the Add Query button.
Name the query and click Create.
Specify the SQL code in the SQL Query field and Save the query configuration. In the example below a public dataset to test the extractor was used: