Reference

Create BigQuery Dataset

Creates a new BigQuery dataset with specified location, labels, and description to organize and store your analytics data. Use this when you need to set up dedicated storage for different data projects while ensuring data residency requirements are met.

Create BigQuery Table

Set up a new table in BigQuery to organize and structure your data for analysis and reporting. This operation lets you configure how data is stored, partitioned, and accessed to optimize performance and cost.

Get BigQuery Query Results

Retrieves the results and status of a BigQuery query job, allowing you to fetch completed analysis data or check if a long-running query has finished processing.

Insert Data into BigQuery Table

Stream individual or small batches of records directly into BigQuery tables for immediate availability without waiting for load jobs to complete. Ideal for real-time data ingestion with built-in deduplication and error handling.

List BigQuery Datasets

View all datasets available in your BigQuery project along with their locations to understand your data structure and plan queries accordingly. This helps you identify which datasets are accessible before running analysis.

List BigQuery Table Data

Retrieve and browse actual data from your BigQuery tables without writing SQL queries, getting results in an easy-to-read row format. Perfect for quickly inspecting data or extracting specific information from your datasets.

Cancel BigQuery Job

Stop a running BigQuery job that's taking longer than expected or consuming excessive resources, allowing you to avoid unnecessary costs and free up processing capacity. The job stops immediately, though you'll need to check its status to confirm the cancellation completed.

Create Analytics Hub Data Exchange

Set up a shareable container in Google BigQuery where you can organize and publish datasets for controlled distribution to partners, clients, or team members. This enables you to manage who accesses specific data and maintain a centralized hub for all your data sharing activities.

Create Analytics Hub Listing

Publish a BigQuery dataset as a discoverable listing in Analytics Hub so that partners, customers, or internal teams can find and subscribe to your data products. This enables you to monetize data assets or streamline data sharing across your organization.

Create Analytics Hub Listing

Publish a BigQuery dataset to a data exchange so other users and organizations can discover and subscribe to your data. This enables you to monetize or share your datasets within a controlled marketplace environment.

Create Analytics Hub Query Template

Create reusable query templates in BigQuery Analytics Hub Data Clean Rooms to standardize and pre-approve data queries for secure data sharing with clients or partners. This ensures consistent, compliant data access across your organization.

Create BigQuery Connection

Set up a new BigQuery connection to external data sources like AWS, Azure, Cloud Spanner, Cloud SQL, Salesforce DataCloud, or Apache Spark, enabling you to query and analyze data stored outside of BigQuery.

Create BigQuery Data Policy (v2beta1)

Set up automatic data masking and column-level security rules to protect sensitive information in your BigQuery datasets. This ensures that only authorized team members can view confidential data like customer emails, financial details, or personal identifiers.

Create BigQuery Reservation

Reserve dedicated compute capacity in BigQuery to guarantee consistent performance for your analytics queries and ensure predictable costs regardless of demand fluctuations.

Create BigQuery Reservation Assignment

Allocate BigQuery processing resources to a specific project, folder, or organization by linking them to a reserved capacity pool, enabling predictable performance for your analytics workloads.

Create BigQuery Routine

Create reusable functions or procedures in BigQuery to encapsulate custom business logic, data transformations, and calculations that can be called across multiple queries and projects. This enables consistent data processing and reduces code duplication across your analytics workflows.

Create Capacity Commitment

Purchases dedicated compute capacity (slots) for BigQuery with flexible commitment periods, ensuring predictable costs and priority performance for your data analytics workloads.

Delete BigQuery Dataset

Permanently removes a BigQuery dataset and optionally all tables within it, allowing you to clean up unused data storage and free up resources. Use this when you no longer need historical data, want to reorganize your data structure, or need to reclaim space from test environments.

Delete BigQuery Job Metadata

Removes job metadata and history records from BigQuery to clean up your data warehouse and free up storage space. This is useful when you want to permanently delete information about completed jobs and their associated child jobs from your system.

Delete BigQuery ML Model

Permanently removes a trained machine learning model from your BigQuery dataset when you no longer need it, freeing up storage and keeping your project organized.

Delete BigQuery Routine

Remove a stored procedure, user-defined function, or table function from your BigQuery dataset when it's no longer needed or needs to be replaced with updated logic.

Delete BigQuery Table

Permanently removes a BigQuery table and all its data from your dataset, which is useful for cleaning up obsolete data or freeing up storage after data analysis is complete.

Get BigQuery Connection IAM Policy

Retrieve the access control settings for a BigQuery connection to see who has permission to use it and what actions they can perform.

Get BigQuery Dataset Metadata

Retrieve detailed information about a BigQuery dataset including its location, creation date, and configuration settings to ensure your queries and jobs are set up correctly.

Get BigQuery Job

Retrieve detailed information about a BigQuery job including its current status, configuration, and execution statistics. Use this to monitor query progress, verify job completion, and troubleshoot data processing issues.

Get BigQuery ML Model

Retrieve detailed information about a trained machine learning model in BigQuery, including its configuration, performance metrics, and training details. This helps you understand and validate your ML models before using them for predictions.

Get BigQuery Routine

Retrieve details about a specific BigQuery routine including its definition, parameters, and return type to understand how it works or verify its configuration.

Get BigQuery Routine IAM Policy

Check who has access to a BigQuery routine and what permissions they have, helping you verify current access controls before making changes.

Get BigQuery Service Account

Retrieves the service account email associated with your BigQuery project, which you need when setting up encryption, managing permissions, or integrating with other Google Cloud services.

Get BigQuery Table IAM Policy

Retrieve the current access permissions and roles assigned to a specific BigQuery table so you can audit who has access and verify permissions before making changes.

Get BigQuery Table Schema

Retrieve the structure and column information of a BigQuery table to understand its layout and data types before writing queries. This helps you avoid errors and work confidently with your data without needing to run expensive queries or have special database permissions.

Insert BigQuery Job

Starts a new BigQuery job to run queries, load data from cloud storage, extract data to files, or copy tables asynchronously. This lets you process large datasets without waiting for results to complete.

Insert BigQuery Job with Upload

Uploads a file directly into a BigQuery table in one operation, eliminating the need to first store it in Cloud Storage. This streamlines getting your data into BigQuery for analysis and reporting.

List Analytics Hub Listings

Discover and browse all available data listings within a Google BigQuery Analytics Hub data exchange to identify datasets you can subscribe to and use in your analytics.

List Analytics Hub Query Templates

Discover all available query templates in your Analytics Hub data exchange to find pre-built, approved queries for analyzing shared datasets. This helps you quickly access standardized data queries without writing them from scratch.

List BigQuery Capacity Commitments

View all your purchased BigQuery compute capacity commitments and their details, including plan type, status, and duration. This helps you track your compute resource investments and understand your current capacity allocations.

List BigQuery Connections

Retrieve all external data source connections configured in your BigQuery project, such as Cloud SQL, AWS, or Azure integrations. This helps you discover and manage all available data connections without manually searching through your setup.

List BigQuery Data Transfer Locations

Retrieves all available geographic regions where you can set up BigQuery data transfers, helping you understand where your data operations can be executed.

List BigQuery Jobs

Retrieve and monitor all BigQuery jobs you've run in your project, sorted by most recent first, to track query execution and job performance over time. This helps you understand data processing activity and troubleshoot any failed analyses.

List BigQuery Location Data Policies

Retrieve all data policies applied to your BigQuery datasets in a specific location, helping you understand what masking and security controls are currently configured.

List BigQuery Models

Retrieve all machine learning models stored in a specific BigQuery dataset to see what predictive models and analyses are available. This helps you discover existing models before using them for analysis or predictions.

List BigQuery Projects

Retrieve all BigQuery projects you have access to, enabling you to see which datasets and tables are available across your organization's analytics infrastructure.

List BigQuery Reservation Assignments

View all the computing resource assignments you've set up across your BigQuery reservations to understand how your query processing capacity is distributed. This helps you track which projects and workloads are using your reserved slots.

List BigQuery Reservation Groups

Retrieve all BigQuery reservation groups available in your project for a specific location, helping you understand your current resource allocation setup. This lets you see which reservation containers are active and available for organizing your query processing capacity.

List BigQuery Reservations

Retrieve all BigQuery reservations available in your project within a specific location, including their slot capacity and autoscaling settings. Use this to understand your current reserved computing resources and their configurations.

List BigQuery Routines

Discover all user-defined functions and stored procedures available in your BigQuery dataset so you can understand what data transformation logic is already built and ready to use.

List BigQuery Row Access Policies

Retrieve all row-level security policies applied to a BigQuery table to understand data access restrictions and filter rules. This helps you audit and verify that sensitive data is properly protected.

List BigQuery Tables

Tool to list tables in a BigQuery dataset via the REST API.

List Connections in Location

Retrieve all external data source connections configured in BigQuery for a specific location, helping you discover available Cloud SQL, AWS, Azure, Spark, and other data integrations.

List Data Exchange Listings

Discover and explore all available data listings within a specific Analytics Hub data exchange to identify datasets you can subscribe to for data sharing and analysis.

List Organization Data Exchanges

Discover and browse all available data exchanges within your organization across different locations, helping you identify shared datasets and data products you can access or subscribe to.

Patch BigQuery Dataset

Tool to update an existing BigQuery dataset using RFC5789 PATCH semantics.

Patch BigQuery ML Model

Tool to update specific fields in an existing BigQuery ML model using PATCH semantics.

Patch BigQuery Table

Tool to update specific fields in an existing BigQuery table using RFC5789 PATCH semantics.

Query

Query Tool runs a SQL query in BigQuery using the REST API.

Search All BigQuery Reservation Assignments

Tool to search all BigQuery reservation assignments for a specified resource in a particular region.

Set BigQuery Routine IAM Policy

Tool to set the IAM access control policy for a BigQuery routine resource.

Test BigQuery Routine IAM Permissions

Tool to test which IAM permissions the caller has on a BigQuery routine.

Undelete BigQuery Dataset

Tool to undelete a BigQuery dataset within the time travel window.

Update BigQuery Connection

Tool to update a specified BigQuery connection using the BigQuery Connection API.

Update BigQuery Dataset

Tool to update information in an existing BigQuery dataset using the PUT method.

Update BigQuery Routine

Tool to update an existing BigQuery routine (function or stored procedure).

Update BigQuery Table

Tool to update an existing BigQuery table.