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Manage BigQuery API dependencies
This document describes the Google Cloud services and APIs that
BigQuery depends on. It also explains the effects on
BigQuery behavior when you disable those services. Review this
document before you enable or disable services in your project.
Some services are enabled by default in every Google Cloud project that you create.
Other APIs are automatically enabled for all Google Cloud projects that use
BigQuery. The remaining services must be explicitly enabled
before you can use their functionality. For more information, see the
following resources:
You can't create new or access previously created profile
insights, data quality scans, or query suggestions.
You can't see data asset details on a lineage graph.
You can't search for data assets in data canvas.
Services enabled by BigQuery Unified API
The BigQuery Unified API (bigqueryunified.googleapis.com)
includes a curated collection of services that are required for various
BigQuery features to function. If you enable the
BigQuery Unified API, then all of these services are activated
simultaneously. Google can update the services in this collection, and those
services are automatically enabled in projects with this API enabled.
You can disable individual services and APIs.
Any existing BigQuery ML remote models stop
working.
Your existing notebooks remain accessible for editing.
bigqueryunified.googleapis.com
Provides a single-click activation of the BigQuery
dependent services listed in this document, excluding the
cloudaicompanion, composer and
datalineage APIs.
Ensures new BigQuery dependencies are enabled in
your project.
Future dependencies aren't automatically enabled in your
project.
compute.googleapis.com
Google Compute Engine provides a runtime environment for all
features provided by Dataproc and Vertex AI.
Colab notebooks, remote ML models,
Apache Spark, SparkSQL, and PySpark jobs stop.
To learn how to manage API access at a granular level with organization
policy constraints, see
Restricting resource usage.
To learn how to control access to services with
Identity and Access Management (IAM) roles and permissions for
BigQuery, see
BigQuery IAM roles and permissions.
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