genai-toolbox/docs/en/resources/sources/bigquery.md

title, type, weight, description

title	type	weight	description
BigQuery	docs	1	BigQuery is Google Cloud's fully managed, petabyte-scale, and cost-effective analytics data warehouse that lets you run analytics over vast amounts of data in near real time. With BigQuery, there's no infrastructure to set up or manage, letting you focus on finding meaningful insights using GoogleSQL and taking advantage of flexible pricing models across on-demand and flat-rate options.

BigQuery Source

BigQuery is Google Cloud's fully managed, petabyte-scale, and cost-effective analytics data warehouse that lets you run analytics over vast amounts of data in near real time. With BigQuery, there's no infrastructure to set up or manage, letting you focus on finding meaningful insights using GoogleSQL and taking advantage of flexible pricing models across on-demand and flat-rate options.

If you are new to BigQuery, you can try to load and query data with the bq tool.

BigQuery uses GoogleSQL for querying data. GoogleSQL is an ANSI-compliant structured query language (SQL) that is also implemented for other Google Cloud services. SQL queries are handled by cluster nodes in the same way as NoSQL data requests. Therefore, the same best practices apply when creating SQL queries to run against your BigQuery data, such as avoiding full table scans or complex filters.

Available Tools

• bigquery-sql
  Run SQL queries directly against BigQuery datasets.

• bigquery-execute-sql
  Execute structured queries using parameters.

• bigquery-get-dataset-info
  Retrieve metadata for a specific dataset.

• bigquery-get-table-info
  Retrieve metadata for a specific table.

• bigquery-list-dataset-ids
  List available dataset IDs.

• bigquery-list-table-ids
  List tables in a given dataset.

Requirements

IAM Permissions

BigQuery uses Identity and Access Management (IAM) to control user and group access to BigQuery resources like projects, datasets, and tables. Toolbox will use your Application Default Credentials (ADC) to authorize and authenticate when interacting with BigQuery.

In addition to setting the ADC for your server, you need to ensure the IAM identity has been given the correct IAM permissions for the queries you intend to run. Common roles include roles/bigquery.user (which includes permissions to run jobs and read data) or roles/bigquery.dataViewer. See Introduction to BigQuery IAM for more information on applying IAM permissions and roles to an identity.

Example

sources:
  my-bigquery-source:
    kind: "bigquery"
    project: "my-project-id"

Reference

field	type	required	description
kind	string	true	Must be "bigquery".
project	string	true	Id of the GCP project that the cluster was created in (e.g. "my-project-id").
location	string	false	Specifies the location (e.g., 'us', 'asia-northeast1') in which to run the query job. This location must match the location of any tables referenced in the query. The default behavior is for it to be executed in the US multi-region