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93 lines
2.8 KiB
Plaintext
93 lines
2.8 KiB
Plaintext
---
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title: Google BigQuery
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hide_title: true
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sidebar_position: 20
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version: 1
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---
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## Google BigQuery
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The recommended connector library for BigQuery is
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[sqlalchemy-bigquery](https://github.com/googleapis/python-bigquery-sqlalchemy).
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### Install BigQuery Driver
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Follow the steps [here](/docs/databases/docker-add-drivers) about how to
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install new database drivers when setting up Superset locally via docker compose.
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```
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echo "sqlalchemy-bigquery" >> ./docker/requirements-local.txt
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```
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### Connecting to BigQuery
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When adding a new BigQuery connection in Superset, you'll need to add the GCP Service Account
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credentials file (as a JSON).
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1. Create your Service Account via the Google Cloud Platform control panel, provide it access to the
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appropriate BigQuery datasets, and download the JSON configuration file for the service account.
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2. In Superset, you can either upload that JSON or add the JSON blob in the following format (this should be the content of your credential JSON file):
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```
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{
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"type": "service_account",
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"project_id": "...",
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"private_key_id": "...",
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"private_key": "...",
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"client_email": "...",
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"client_id": "...",
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"auth_uri": "...",
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"token_uri": "...",
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"auth_provider_x509_cert_url": "...",
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"client_x509_cert_url": "..."
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}
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```
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3. Additionally, can connect via SQLAlchemy URI instead
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The connection string for BigQuery looks like:
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```
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bigquery://{project_id}
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```
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Go to the **Advanced** tab, Add a JSON blob to the **Secure Extra** field in the database configuration form with
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the following format:
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```
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{
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"credentials_info": <contents of credentials JSON file>
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}
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```
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The resulting file should have this structure:
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```
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{
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"credentials_info": {
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"type": "service_account",
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"project_id": "...",
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"private_key_id": "...",
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"private_key": "...",
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"client_email": "...",
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"client_id": "...",
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"auth_uri": "...",
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"token_uri": "...",
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"auth_provider_x509_cert_url": "...",
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"client_x509_cert_url": "..."
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}
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}
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```
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You should then be able to connect to your BigQuery datasets.
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To be able to upload CSV or Excel files to BigQuery in Superset, you'll need to also add the
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[pandas_gbq](https://github.com/pydata/pandas-gbq) library.
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Currently, Google BigQuery python sdk is not compatible with `gevent`, due to some dynamic monkeypatching on python core library by `gevent`.
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So, when you deploy Superset with `gunicorn` server, you have to use worker type except `gevent`.
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