Google BigQuery

Datasets

Datasets allow you to organize and control access to your tables. For more information, see Datasets.

For a list of methods for this resource, see the end of this page.

Resource representations

{
  "kind": "bigquery#dataset",
  "etag": etag,
  "id": string,
  "selfLink": string,
  "datasetReference": {
    "datasetId": string,
    "projectId": string
  },
  "friendlyName": string,
  "description": string,
  "access": [
    {
      "role": string,
      "userByEmail": string,
      "groupByEmail": string,
      "domain": string,
      "specialGroup": string
    }
  ],
  "creationTime": long,
  "lastModifiedTime": long
}
Property name Value Description Notes
access[] list [Optional] An array of objects that define dataset access for one or more entities. You can set this property when inserting or updating a dataset in order to control who is allowed to access the data. If unspecified at dataset creation time, BigQuery adds default dataset access for the following entities:

  • access.specialGroup: projectReaders; access.role: READER
  • access.specialGroup: projectWriters; access.role: WRITER
  • access.specialGroup: projectOwners; access.role: OWNER
  • access.userByEmail: [dataset creator email]; access.role: OWNER;
For more information about access control in BigQuery, see access control.
access[].domain string [Pick one] A domain to grant access to. Any users signed in with the domain specified will be granted the specified access. Example: "example.com". writable
access[].groupByEmail string [Pick one] An email address of a Google Group to grant access to. writable
access[].role string [Required] Describes the rights granted to the user specified by the other member of the access object. The following string values are supported: READER, WRITER, OWNER.

For more information about access control in BigQuery, see access control.
writable
access[].specialGroup string [Pick one] A special group to grant access to.

Possible values include:
  • projectOwners: Owners of the enclosing project. 
  • projectReaders: Readers of the enclosing project. 
  • projectWriters: Writers of the enclosing project. 
  • allAuthenticatedUsers: All authenticated BigQuery users.
For more information about access control in BigQuery, see access control.
writable
access[].userByEmail string [Pick one] An email address of a user to grant access to. For example: fred@example.com. writable
creationTime long [Output-only] The time when this dataset was created, in milliseconds since the epoch.
datasetReference nested object [Required] A reference that identifies the dataset.
datasetReference.datasetId string [Required] A unique ID for this dataset, without the project name.
datasetReference.projectId string [Optional] The ID of the container project.
description string [Optional] A user-friendly description of the dataset. writable
etag etag [Output-only] A hash of the resource.
friendlyName string [Optional] A descriptive name for the dataset. writable
id string [Output-only] The fully-qualified unique name of the dataset in the format projectId:datasetId. The dataset name without the project name is given in the datasetId field. When creating a new dataset, leave this field blank, and instead specify the datasetId field.
kind string [Output-only] The resource type.
lastModifiedTime long [Output-only] The date when this dataset or any of its tables was last modified, in milliseconds since the epoch.

Methods

The following methods are supported:

delete
Deletes the dataset specified by the datasetId value. Before you can delete a dataset, you must delete all its tables, either manually or by specifying deleteContents. Immediately after deletion, you can create another dataset with the same name.
get
Returns the dataset specified by datasetID.
insert
Creates a new empty dataset.
list
Lists all the datasets in the specified project to which the caller has read access; however, a project owner can list (but not necessarily get) all datasets in his project.
patch
Updates information in an existing dataset. The update method replaces the entire dataset resource, whereas the patch method only replaces fields that are provided in the submitted dataset resource. This method supports patch semantics.
update
Updates information in an existing dataset. The update method replaces the entire dataset resource, whereas the patch method only replaces fields that are provided in the submitted dataset resource.

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