A Singer target that writes data to Google BigQuery.

target-bigquery works together with any other Singer Tap to move data from sources like Braintree, Freshdesk and Hubspot to Google BigQuery.

(originally found in the Google API docs)

1. Use this wizard to create or select a project in the Google Developers Console and activate the BigQuery API. Click Continue, then Go to credentials.
2. On the Add credentials to your project page, click the Cancel button.
3. At the top of the page, select the OAuth consent screen tab. Select an Email address, enter a Product name if not already set, and click the Save button.
4. Select the Credentials tab, click the Create credentials button and select OAuth client ID.
5. Select the application type Other, enter the name "Singer BigQuery Target", and click the Create button.
6. Click OK to dismiss the resulting dialog.
7. Click the Download button to the right of the client ID.
8. Move this file to your working directory and rename it client_secrets.json.

Create a file called config.json in your working directory, following config.sample.json. The required parameters are the project name project_id, the dataset name dataset_id, and table name table_id.

First, make sure Python 3 is installed on your system or follow these installation instructions for Mac or Ubuntu.

target-bigquery can be run with any Singer Tap, but we'll use tap-fixerio - which pulls currency exchange rate data from a public data set - as an example.

These commands will install tap-fixerio and target-bigquery with pip and then run them together, piping the output of tap-fixerio to target-bigquery:

› pip install target-bigquery tap-fixerio
› tap-fixerio | target-bigquery -c config.json
  INFO Replicating the latest exchange rate data from fixer.io
  INFO Tap exiting normally

If you're using a different Tap, substitute tap-fixerio in the final command above to the command used to run your Tap.

It is recommended to use target-bigquery with a service account.

• Download the client_secrets.json file for your service account, and place it on the machine where target-bigquery will be executed.
• Set a GOOGLE_APPLICATION_CREDENTIALS environment variable on the machine, where the value is the fully qualified path to client_secrets.json

It should be possible to use the oAuth flow to authenticate to GCP as well:

• target-bigquery will attempt to open a new window or tab in your default browser. If this fails, copy the URL from the console and manually open it in your browser.
• If you are not already logged into your Google account, you will be prompted to log in.
• If you are logged into multiple Google accounts, you will be asked to select one account to use for the authorization.
• Click the Accept button to allow target-bigquery to access your Google BigQuery table.
• You can close the tab after the signup flow is complete.

The data will be written to the table specified in your config.json.

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