Vertex AI Feature Group.
To get more information about FeatureGroup, see:
resource "google_vertex_ai_feature_group" "feature_group" {
name = "example_feature_group"
description = "A sample feature group"
region = "us-central1"
labels = {
label-one = "value-one"
}
big_query {
big_query_source {
# The source table must have a column named 'feature_timestamp' of type TIMESTAMP.
input_uri = "bq://${google_bigquery_table.sample_table.project}.${google_bigquery_table.sample_table.dataset_id}.${google_bigquery_table.sample_table.table_id}"
}
entity_id_columns = ["feature_id"]
}
}
resource "google_bigquery_dataset" "sample_dataset" {
dataset_id = "job_load_dataset"
friendly_name = "test"
description = "This is a test description"
location = "US"
}
resource "google_bigquery_table" "sample_table" {
deletion_protection = false
dataset_id = google_bigquery_dataset.sample_dataset.dataset_id
table_id = "job_load_table"
schema = <<EOF
[
{
"name": "feature_id",
"type": "STRING",
"mode": "NULLABLE"
},
{
"name": "feature_timestamp",
"type": "TIMESTAMP",
"mode": "NULLABLE"
}
]
EOF
}
The following arguments are supported:
name
-
(Optional)
The resource name of the Feature Group.
labels
-
(Optional)
The labels with user-defined metadata to organize your FeatureGroup.
Note: This field is non-authoritative, and will only manage the labels present in your configuration.
Please refer to the field effective_labels
for all of the labels present on the resource.
description
-
(Optional)
The description of the FeatureGroup.
big_query
-
(Optional)
Indicates that features for this group come from BigQuery Table/View. By default treats the source as a sparse time series source, which is required to have an entityId and a feature_timestamp column in the source.
Structure is documented below.
region
-
(Optional)
The region of feature group. eg us-central1
project
- (Optional) The ID of the project in which the resource belongs.
If it is not provided, the provider project is used.
big_query_source
-
(Required)
The BigQuery source URI that points to either a BigQuery Table or View.
Structure is documented below.
entity_id_columns
-
(Optional)
Columns to construct entityId / row keys. Currently only supports 1 entity_id_column. If not provided defaults to entityId.
The big_query_source
block supports:
input_uri
-
(Required)
BigQuery URI to a table, up to 2000 characters long. For example: bq://projectId.bqDatasetId.bqTableId.
In addition to the arguments listed above, the following computed attributes are exported:
id
- an identifier for the resource with format projects/{{project}}/locations/{{region}}/featureGroups/{{name}}
create_time
-
The timestamp of when the FeatureGroup was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
update_time
-
The timestamp of when the FeatureGroup was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
etag
-
Used to perform consistent read-modify-write updates.
terraform_labels
-
The combination of labels configured directly on the resource
and default labels configured on the provider.
effective_labels
-
All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Terraform, other clients and services.
This resource provides the following Timeouts configuration options:
create
- Default is 20 minutes.update
- Default is 20 minutes.delete
- Default is 20 minutes.FeatureGroup can be imported using any of these accepted formats:
projects/{{project}}/locations/{{region}}/featureGroups/{{name}}
{{project}}/{{region}}/{{name}}
{{region}}/{{name}}
{{name}}
In Terraform v1.5.0 and later, use an import
block to import FeatureGroup using one of the formats above. For example:
import {
id = "projects/{{project}}/locations/{{region}}/featureGroups/{{name}}"
to = google_vertex_ai_feature_group.default
}
When using the terraform import
command, FeatureGroup can be imported using one of the formats above. For example:
$ terraform import google_vertex_ai_feature_group.default projects/{{project}}/locations/{{region}}/featureGroups/{{name}}
$ terraform import google_vertex_ai_feature_group.default {{project}}/{{region}}/{{name}}
$ terraform import google_vertex_ai_feature_group.default {{region}}/{{name}}
$ terraform import google_vertex_ai_feature_group.default {{name}}
This resource supports User Project Overrides.