---
title: Getting Started with Datadog
description: Datadog, the leading service for cloud-scale monitoring.
breadcrumbs: Docs > Infrastructure > Datadog Resource Catalog
---

# gcp_aiplatform_feature_group{% #gcp_aiplatform_feature_group %}

## `ancestors`{% #ancestors %}

**Type**: `UNORDERED_LIST_STRING`

## `big_query`{% #big_query %}

**Type**: `STRUCT`**Provider name**: `bigQuery`**Description**: Indicates that features for this group come from BigQuery Table/View. By default treats the source as a sparse time series source. The BigQuery source table or view must have at least one entity ID column and a column named `feature_timestamp`.

- `big_query_source`**Type**: `STRUCT`**Provider name**: `bigQuerySource`**Description**: Required. Immutable. The BigQuery source URI that points to either a BigQuery Table or View.
  - `input_uri`**Type**: `STRING`**Provider name**: `inputUri`**Description**: Required. BigQuery URI to a table, up to 2000 characters long. Accepted forms: * BigQuery path. For example: `bq://projectId.bqDatasetId.bqTableId`.
- `dense`**Type**: `BOOLEAN`**Provider name**: `dense`**Description**: Optional. If set, all feature values will be fetched from a single row per unique entityId including nulls. If not set, will collapse all rows for each unique entityId into a singe row with any non-null values if present, if no non-null values are present will sync null. ex: If source has schema `(entity_id, feature_timestamp, f0, f1)` and the following rows: `(e1, 2020-01-01T10:00:00.123Z, 10, 15)` `(e1, 2020-02-01T10:00:00.123Z, 20, null)` If dense is set, `(e1, 20, null)` is synced to online stores. If dense is not set, `(e1, 20, 15)` is synced to online stores.
- `entity_id_columns`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `entityIdColumns`**Description**: Optional. Columns to construct entity_id / row keys. If not provided defaults to `entity_id`.
- `static_data_source`**Type**: `BOOLEAN`**Provider name**: `staticDataSource`**Description**: Optional. Set if the data source is not a time-series.
- `time_series`**Type**: `STRUCT`**Provider name**: `timeSeries`**Description**: Optional. If the source is a time-series source, this can be set to control how downstream sources (ex: FeatureView ) will treat time-series sources. If not set, will treat the source as a time-series source with `feature_timestamp` as timestamp column and no scan boundary.
  - `timestamp_column`**Type**: `STRING`**Provider name**: `timestampColumn`**Description**: Optional. Column hosting timestamp values for a time-series source. Will be used to determine the latest `feature_values` for each entity. Optional. If not provided, column named `feature_timestamp` of type `TIMESTAMP` will be used.

## `create_time`{% #create_time %}

**Type**: `TIMESTAMP`**Provider name**: `createTime`**Description**: Output only. Timestamp when this FeatureGroup was created.

## `description`{% #description %}

**Type**: `STRING`**Provider name**: `description`**Description**: Optional. Description of the FeatureGroup.

## `etag`{% #etag %}

**Type**: `STRING`**Provider name**: `etag`**Description**: Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

## `labels`{% #labels %}

**Type**: `UNORDERED_LIST_STRING`

## `name`{% #name %}

**Type**: `STRING`**Provider name**: `name`**Description**: Identifier. Name of the FeatureGroup. Format: `projects/{project}/locations/{location}/featureGroups/{featureGroup}`

## `organization_id`{% #organization_id %}

**Type**: `STRING`

## `parent`{% #parent %}

**Type**: `STRING`

## `project_id`{% #project_id %}

**Type**: `STRING`

## `project_number`{% #project_number %}

**Type**: `STRING`

## `region_id`{% #region_id %}

**Type**: `STRING`

## `resource_name`{% #resource_name %}

**Type**: `STRING`

## `service_account_email`{% #service_account_email %}

**Type**: `STRING`**Provider name**: `serviceAccountEmail`**Description**: Output only. A Service Account unique to this FeatureGroup. The role bigquery.dataViewer should be granted to this service account to allow Vertex AI Feature Store to access source data while running jobs under this FeatureGroup.

## `service_agent_type`{% #service_agent_type %}

**Type**: `STRING`**Provider name**: `serviceAgentType`**Description**: Optional. Service agent type used during jobs under a FeatureGroup. By default, the Vertex AI Service Agent is used. When using an IAM Policy to isolate this FeatureGroup within a project, a separate service account should be provisioned by setting this field to `SERVICE_AGENT_TYPE_FEATURE_GROUP`. This will generate a separate service account to access the BigQuery source table.**Possible values**:

- `SERVICE_AGENT_TYPE_UNSPECIFIED` - By default, the project-level Vertex AI Service Agent is enabled.
- `SERVICE_AGENT_TYPE_PROJECT` - Specifies the project-level Vertex AI Service Agent ([https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents)](https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents%29).
- `SERVICE_AGENT_TYPE_FEATURE_GROUP` - Enable a FeatureGroup service account to be created by Vertex AI and output in the field `service_account_email`. This service account will be used to read from the source BigQuery table during jobs under a FeatureGroup.

## `tags`{% #tags %}

**Type**: `UNORDERED_LIST_STRING`

## `update_time`{% #update_time %}

**Type**: `TIMESTAMP`**Provider name**: `updateTime`**Description**: Output only. Timestamp when this FeatureGroup was last updated.

## `zone_id`{% #zone_id %}

**Type**: `STRING`