gcp.vertex.AiFeatureGroup
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Vertex AI Feature Group.
To get more information about FeatureGroup, see:
- API documentation
- How-to Guides
Example Usage
Vertex Ai Feature Group
import * as pulumi from "@pulumi/pulumi";
import * as gcp from "@pulumi/gcp";
const sampleDataset = new gcp.bigquery.Dataset("sample_dataset", {
    datasetId: "job_load_dataset",
    friendlyName: "test",
    description: "This is a test description",
    location: "US",
});
const sampleTable = new gcp.bigquery.Table("sample_table", {
    deletionProtection: false,
    datasetId: sampleDataset.datasetId,
    tableId: "job_load_table",
    schema: `[
    {
        "name": "feature_id",
        "type": "STRING",
        "mode": "NULLABLE"
    },
    {
        "name": "feature_timestamp",
        "type": "TIMESTAMP",
        "mode": "NULLABLE"
    }
]
`,
});
const featureGroup = new gcp.vertex.AiFeatureGroup("feature_group", {
    name: "example_feature_group",
    description: "A sample feature group",
    region: "us-central1",
    labels: {
        "label-one": "value-one",
    },
    bigQuery: {
        bigQuerySource: {
            inputUri: pulumi.interpolate`bq://${sampleTable.project}.${sampleTable.datasetId}.${sampleTable.tableId}`,
        },
        entityIdColumns: ["feature_id"],
    },
});
import pulumi
import pulumi_gcp as gcp
sample_dataset = gcp.bigquery.Dataset("sample_dataset",
    dataset_id="job_load_dataset",
    friendly_name="test",
    description="This is a test description",
    location="US")
sample_table = gcp.bigquery.Table("sample_table",
    deletion_protection=False,
    dataset_id=sample_dataset.dataset_id,
    table_id="job_load_table",
    schema="""[
    {
        "name": "feature_id",
        "type": "STRING",
        "mode": "NULLABLE"
    },
    {
        "name": "feature_timestamp",
        "type": "TIMESTAMP",
        "mode": "NULLABLE"
    }
]
""")
feature_group = gcp.vertex.AiFeatureGroup("feature_group",
    name="example_feature_group",
    description="A sample feature group",
    region="us-central1",
    labels={
        "label-one": "value-one",
    },
    big_query={
        "big_query_source": {
            "input_uri": pulumi.Output.all(
                project=sample_table.project,
                dataset_id=sample_table.dataset_id,
                table_id=sample_table.table_id
).apply(lambda resolved_outputs: f"bq://{resolved_outputs['project']}.{resolved_outputs['dataset_id']}.{resolved_outputs['table_id']}")
,
        },
        "entity_id_columns": ["feature_id"],
    })
package main
import (
	"fmt"
	"github.com/pulumi/pulumi-gcp/sdk/v8/go/gcp/bigquery"
	"github.com/pulumi/pulumi-gcp/sdk/v8/go/gcp/vertex"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)
func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		sampleDataset, err := bigquery.NewDataset(ctx, "sample_dataset", &bigquery.DatasetArgs{
			DatasetId:    pulumi.String("job_load_dataset"),
			FriendlyName: pulumi.String("test"),
			Description:  pulumi.String("This is a test description"),
			Location:     pulumi.String("US"),
		})
		if err != nil {
			return err
		}
		sampleTable, err := bigquery.NewTable(ctx, "sample_table", &bigquery.TableArgs{
			DeletionProtection: pulumi.Bool(false),
			DatasetId:          sampleDataset.DatasetId,
			TableId:            pulumi.String("job_load_table"),
			Schema: pulumi.String(`[
    {
        "name": "feature_id",
        "type": "STRING",
        "mode": "NULLABLE"
    },
    {
        "name": "feature_timestamp",
        "type": "TIMESTAMP",
        "mode": "NULLABLE"
    }
]
`),
		})
		if err != nil {
			return err
		}
		_, err = vertex.NewAiFeatureGroup(ctx, "feature_group", &vertex.AiFeatureGroupArgs{
			Name:        pulumi.String("example_feature_group"),
			Description: pulumi.String("A sample feature group"),
			Region:      pulumi.String("us-central1"),
			Labels: pulumi.StringMap{
				"label-one": pulumi.String("value-one"),
			},
			BigQuery: &vertex.AiFeatureGroupBigQueryArgs{
				BigQuerySource: &vertex.AiFeatureGroupBigQueryBigQuerySourceArgs{
					InputUri: pulumi.All(sampleTable.Project, sampleTable.DatasetId, sampleTable.TableId).ApplyT(func(_args []interface{}) (string, error) {
						project := _args[0].(string)
						datasetId := _args[1].(string)
						tableId := _args[2].(string)
						return fmt.Sprintf("bq://%v.%v.%v", project, datasetId, tableId), nil
					}).(pulumi.StringOutput),
				},
				EntityIdColumns: pulumi.StringArray{
					pulumi.String("feature_id"),
				},
			},
		})
		if err != nil {
			return err
		}
		return nil
	})
}
using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Gcp = Pulumi.Gcp;
return await Deployment.RunAsync(() => 
{
    var sampleDataset = new Gcp.BigQuery.Dataset("sample_dataset", new()
    {
        DatasetId = "job_load_dataset",
        FriendlyName = "test",
        Description = "This is a test description",
        Location = "US",
    });
    var sampleTable = new Gcp.BigQuery.Table("sample_table", new()
    {
        DeletionProtection = false,
        DatasetId = sampleDataset.DatasetId,
        TableId = "job_load_table",
        Schema = @"[
    {
        ""name"": ""feature_id"",
        ""type"": ""STRING"",
        ""mode"": ""NULLABLE""
    },
    {
        ""name"": ""feature_timestamp"",
        ""type"": ""TIMESTAMP"",
        ""mode"": ""NULLABLE""
    }
]
",
    });
    var featureGroup = new Gcp.Vertex.AiFeatureGroup("feature_group", new()
    {
        Name = "example_feature_group",
        Description = "A sample feature group",
        Region = "us-central1",
        Labels = 
        {
            { "label-one", "value-one" },
        },
        BigQuery = new Gcp.Vertex.Inputs.AiFeatureGroupBigQueryArgs
        {
            BigQuerySource = new Gcp.Vertex.Inputs.AiFeatureGroupBigQueryBigQuerySourceArgs
            {
                InputUri = Output.Tuple(sampleTable.Project, sampleTable.DatasetId, sampleTable.TableId).Apply(values =>
                {
                    var project = values.Item1;
                    var datasetId = values.Item2;
                    var tableId = values.Item3;
                    return $"bq://{project}.{datasetId}.{tableId}";
                }),
            },
            EntityIdColumns = new[]
            {
                "feature_id",
            },
        },
    });
});
package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.gcp.bigquery.Dataset;
import com.pulumi.gcp.bigquery.DatasetArgs;
import com.pulumi.gcp.bigquery.Table;
import com.pulumi.gcp.bigquery.TableArgs;
import com.pulumi.gcp.vertex.AiFeatureGroup;
import com.pulumi.gcp.vertex.AiFeatureGroupArgs;
import com.pulumi.gcp.vertex.inputs.AiFeatureGroupBigQueryArgs;
import com.pulumi.gcp.vertex.inputs.AiFeatureGroupBigQueryBigQuerySourceArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;
public class App {
    public static void main(String[] args) {
        Pulumi.run(App::stack);
    }
    public static void stack(Context ctx) {
        var sampleDataset = new Dataset("sampleDataset", DatasetArgs.builder()
            .datasetId("job_load_dataset")
            .friendlyName("test")
            .description("This is a test description")
            .location("US")
            .build());
        var sampleTable = new Table("sampleTable", TableArgs.builder()
            .deletionProtection(false)
            .datasetId(sampleDataset.datasetId())
            .tableId("job_load_table")
            .schema("""
[
    {
        "name": "feature_id",
        "type": "STRING",
        "mode": "NULLABLE"
    },
    {
        "name": "feature_timestamp",
        "type": "TIMESTAMP",
        "mode": "NULLABLE"
    }
]
            """)
            .build());
        var featureGroup = new AiFeatureGroup("featureGroup", AiFeatureGroupArgs.builder()
            .name("example_feature_group")
            .description("A sample feature group")
            .region("us-central1")
            .labels(Map.of("label-one", "value-one"))
            .bigQuery(AiFeatureGroupBigQueryArgs.builder()
                .bigQuerySource(AiFeatureGroupBigQueryBigQuerySourceArgs.builder()
                    .inputUri(Output.tuple(sampleTable.project(), sampleTable.datasetId(), sampleTable.tableId()).applyValue(values -> {
                        var project = values.t1;
                        var datasetId = values.t2;
                        var tableId = values.t3;
                        return String.format("bq://%s.%s.%s", project,datasetId,tableId);
                    }))
                    .build())
                .entityIdColumns("feature_id")
                .build())
            .build());
    }
}
resources:
  featureGroup:
    type: gcp:vertex:AiFeatureGroup
    name: feature_group
    properties:
      name: example_feature_group
      description: A sample feature group
      region: us-central1
      labels:
        label-one: value-one
      bigQuery:
        bigQuerySource:
          inputUri: bq://${sampleTable.project}.${sampleTable.datasetId}.${sampleTable.tableId}
        entityIdColumns:
          - feature_id
  sampleDataset:
    type: gcp:bigquery:Dataset
    name: sample_dataset
    properties:
      datasetId: job_load_dataset
      friendlyName: test
      description: This is a test description
      location: US
  sampleTable:
    type: gcp:bigquery:Table
    name: sample_table
    properties:
      deletionProtection: false
      datasetId: ${sampleDataset.datasetId}
      tableId: job_load_table
      schema: |
        [
            {
                "name": "feature_id",
                "type": "STRING",
                "mode": "NULLABLE"
            },
            {
                "name": "feature_timestamp",
                "type": "TIMESTAMP",
                "mode": "NULLABLE"
            }
        ]        
Create AiFeatureGroup Resource
Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.
Constructor syntax
new AiFeatureGroup(name: string, args?: AiFeatureGroupArgs, opts?: CustomResourceOptions);@overload
def AiFeatureGroup(resource_name: str,
                   args: Optional[AiFeatureGroupArgs] = None,
                   opts: Optional[ResourceOptions] = None)
@overload
def AiFeatureGroup(resource_name: str,
                   opts: Optional[ResourceOptions] = None,
                   big_query: Optional[AiFeatureGroupBigQueryArgs] = None,
                   description: Optional[str] = None,
                   labels: Optional[Mapping[str, str]] = None,
                   name: Optional[str] = None,
                   project: Optional[str] = None,
                   region: Optional[str] = None)func NewAiFeatureGroup(ctx *Context, name string, args *AiFeatureGroupArgs, opts ...ResourceOption) (*AiFeatureGroup, error)public AiFeatureGroup(string name, AiFeatureGroupArgs? args = null, CustomResourceOptions? opts = null)
public AiFeatureGroup(String name, AiFeatureGroupArgs args)
public AiFeatureGroup(String name, AiFeatureGroupArgs args, CustomResourceOptions options)
type: gcp:vertex:AiFeatureGroup
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.
Parameters
- name string
- The unique name of the resource.
- args AiFeatureGroupArgs
- The arguments to resource properties.
- opts CustomResourceOptions
- Bag of options to control resource's behavior.
- resource_name str
- The unique name of the resource.
- args AiFeatureGroupArgs
- The arguments to resource properties.
- opts ResourceOptions
- Bag of options to control resource's behavior.
- ctx Context
- Context object for the current deployment.
- name string
- The unique name of the resource.
- args AiFeatureGroupArgs
- The arguments to resource properties.
- opts ResourceOption
- Bag of options to control resource's behavior.
- name string
- The unique name of the resource.
- args AiFeatureGroupArgs
- The arguments to resource properties.
- opts CustomResourceOptions
- Bag of options to control resource's behavior.
- name String
- The unique name of the resource.
- args AiFeatureGroupArgs
- The arguments to resource properties.
- options CustomResourceOptions
- Bag of options to control resource's behavior.
Constructor example
The following reference example uses placeholder values for all input properties.
var aiFeatureGroupResource = new Gcp.Vertex.AiFeatureGroup("aiFeatureGroupResource", new()
{
    BigQuery = new Gcp.Vertex.Inputs.AiFeatureGroupBigQueryArgs
    {
        BigQuerySource = new Gcp.Vertex.Inputs.AiFeatureGroupBigQueryBigQuerySourceArgs
        {
            InputUri = "string",
        },
        EntityIdColumns = new[]
        {
            "string",
        },
    },
    Description = "string",
    Labels = 
    {
        { "string", "string" },
    },
    Name = "string",
    Project = "string",
    Region = "string",
});
example, err := vertex.NewAiFeatureGroup(ctx, "aiFeatureGroupResource", &vertex.AiFeatureGroupArgs{
	BigQuery: &vertex.AiFeatureGroupBigQueryArgs{
		BigQuerySource: &vertex.AiFeatureGroupBigQueryBigQuerySourceArgs{
			InputUri: pulumi.String("string"),
		},
		EntityIdColumns: pulumi.StringArray{
			pulumi.String("string"),
		},
	},
	Description: pulumi.String("string"),
	Labels: pulumi.StringMap{
		"string": pulumi.String("string"),
	},
	Name:    pulumi.String("string"),
	Project: pulumi.String("string"),
	Region:  pulumi.String("string"),
})
var aiFeatureGroupResource = new AiFeatureGroup("aiFeatureGroupResource", AiFeatureGroupArgs.builder()
    .bigQuery(AiFeatureGroupBigQueryArgs.builder()
        .bigQuerySource(AiFeatureGroupBigQueryBigQuerySourceArgs.builder()
            .inputUri("string")
            .build())
        .entityIdColumns("string")
        .build())
    .description("string")
    .labels(Map.of("string", "string"))
    .name("string")
    .project("string")
    .region("string")
    .build());
ai_feature_group_resource = gcp.vertex.AiFeatureGroup("aiFeatureGroupResource",
    big_query={
        "big_query_source": {
            "input_uri": "string",
        },
        "entity_id_columns": ["string"],
    },
    description="string",
    labels={
        "string": "string",
    },
    name="string",
    project="string",
    region="string")
const aiFeatureGroupResource = new gcp.vertex.AiFeatureGroup("aiFeatureGroupResource", {
    bigQuery: {
        bigQuerySource: {
            inputUri: "string",
        },
        entityIdColumns: ["string"],
    },
    description: "string",
    labels: {
        string: "string",
    },
    name: "string",
    project: "string",
    region: "string",
});
type: gcp:vertex:AiFeatureGroup
properties:
    bigQuery:
        bigQuerySource:
            inputUri: string
        entityIdColumns:
            - string
    description: string
    labels:
        string: string
    name: string
    project: string
    region: string
AiFeatureGroup Resource Properties
To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.
Inputs
In Python, inputs that are objects can be passed either as argument classes or as dictionary literals.
The AiFeatureGroup resource accepts the following input properties:
- BigQuery AiFeature Group Big Query 
- 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.
- Description string
- The description of the FeatureGroup.
- Labels Dictionary<string, string>
- 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_labelsfor all of the labels present on the resource.
- Name string
- The resource name of the Feature Group.
- Project string
- The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
- Region string
- The region of feature group. eg us-central1
- BigQuery AiFeature Group Big Query Args 
- 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.
- Description string
- The description of the FeatureGroup.
- Labels map[string]string
- 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_labelsfor all of the labels present on the resource.
- Name string
- The resource name of the Feature Group.
- Project string
- The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
- Region string
- The region of feature group. eg us-central1
- bigQuery AiFeature Group Big Query 
- 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.
- description String
- The description of the FeatureGroup.
- labels Map<String,String>
- 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_labelsfor all of the labels present on the resource.
- name String
- The resource name of the Feature Group.
- project String
- The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
- region String
- The region of feature group. eg us-central1
- bigQuery AiFeature Group Big Query 
- 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.
- description string
- The description of the FeatureGroup.
- labels {[key: string]: string}
- 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_labelsfor all of the labels present on the resource.
- name string
- The resource name of the Feature Group.
- project string
- The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
- region string
- The region of feature group. eg us-central1
- big_query AiFeature Group Big Query Args 
- 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.
- description str
- The description of the FeatureGroup.
- labels Mapping[str, str]
- 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_labelsfor all of the labels present on the resource.
- name str
- The resource name of the Feature Group.
- project str
- The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
- region str
- The region of feature group. eg us-central1
- bigQuery Property Map
- 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.
- description String
- The description of the FeatureGroup.
- labels Map<String>
- 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_labelsfor all of the labels present on the resource.
- name String
- The resource name of the Feature Group.
- project String
- The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
- region String
- The region of feature group. eg us-central1
Outputs
All input properties are implicitly available as output properties. Additionally, the AiFeatureGroup resource produces the following output properties:
- CreateTime string
- The timestamp of when the FeatureGroup was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- EffectiveLabels Dictionary<string, string>
- All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
- Etag string
- Used to perform consistent read-modify-write updates.
- Id string
- The provider-assigned unique ID for this managed resource.
- PulumiLabels Dictionary<string, string>
- The combination of labels configured directly on the resource and default labels configured on the provider.
- UpdateTime string
- The timestamp of when the FeatureGroup was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- CreateTime string
- The timestamp of when the FeatureGroup was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- EffectiveLabels map[string]string
- All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
- Etag string
- Used to perform consistent read-modify-write updates.
- Id string
- The provider-assigned unique ID for this managed resource.
- PulumiLabels map[string]string
- The combination of labels configured directly on the resource and default labels configured on the provider.
- UpdateTime string
- The timestamp of when the FeatureGroup was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- createTime String
- The timestamp of when the FeatureGroup was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- effectiveLabels Map<String,String>
- All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
- etag String
- Used to perform consistent read-modify-write updates.
- id String
- The provider-assigned unique ID for this managed resource.
- pulumiLabels Map<String,String>
- The combination of labels configured directly on the resource and default labels configured on the provider.
- updateTime String
- The timestamp of when the FeatureGroup was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- createTime string
- The timestamp of when the FeatureGroup was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- effectiveLabels {[key: string]: string}
- All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
- etag string
- Used to perform consistent read-modify-write updates.
- id string
- The provider-assigned unique ID for this managed resource.
- pulumiLabels {[key: string]: string}
- The combination of labels configured directly on the resource and default labels configured on the provider.
- updateTime string
- The timestamp of when the FeatureGroup was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- create_time str
- The timestamp of when the FeatureGroup was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- effective_labels Mapping[str, str]
- All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
- etag str
- Used to perform consistent read-modify-write updates.
- id str
- The provider-assigned unique ID for this managed resource.
- pulumi_labels Mapping[str, str]
- The combination of labels configured directly on the resource and default labels configured on the provider.
- update_time str
- The timestamp of when the FeatureGroup was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- createTime String
- The timestamp of when the FeatureGroup was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- effectiveLabels Map<String>
- All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
- etag String
- Used to perform consistent read-modify-write updates.
- id String
- The provider-assigned unique ID for this managed resource.
- pulumiLabels Map<String>
- The combination of labels configured directly on the resource and default labels configured on the provider.
- updateTime String
- The timestamp of when the FeatureGroup was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
Look up Existing AiFeatureGroup Resource
Get an existing AiFeatureGroup resource’s state with the given name, ID, and optional extra properties used to qualify the lookup.
public static get(name: string, id: Input<ID>, state?: AiFeatureGroupState, opts?: CustomResourceOptions): AiFeatureGroup@staticmethod
def get(resource_name: str,
        id: str,
        opts: Optional[ResourceOptions] = None,
        big_query: Optional[AiFeatureGroupBigQueryArgs] = None,
        create_time: Optional[str] = None,
        description: Optional[str] = None,
        effective_labels: Optional[Mapping[str, str]] = None,
        etag: Optional[str] = None,
        labels: Optional[Mapping[str, str]] = None,
        name: Optional[str] = None,
        project: Optional[str] = None,
        pulumi_labels: Optional[Mapping[str, str]] = None,
        region: Optional[str] = None,
        update_time: Optional[str] = None) -> AiFeatureGroupfunc GetAiFeatureGroup(ctx *Context, name string, id IDInput, state *AiFeatureGroupState, opts ...ResourceOption) (*AiFeatureGroup, error)public static AiFeatureGroup Get(string name, Input<string> id, AiFeatureGroupState? state, CustomResourceOptions? opts = null)public static AiFeatureGroup get(String name, Output<String> id, AiFeatureGroupState state, CustomResourceOptions options)resources:  _:    type: gcp:vertex:AiFeatureGroup    get:      id: ${id}- name
- The unique name of the resulting resource.
- id
- The unique provider ID of the resource to lookup.
- state
- Any extra arguments used during the lookup.
- opts
- A bag of options that control this resource's behavior.
- resource_name
- The unique name of the resulting resource.
- id
- The unique provider ID of the resource to lookup.
- name
- The unique name of the resulting resource.
- id
- The unique provider ID of the resource to lookup.
- state
- Any extra arguments used during the lookup.
- opts
- A bag of options that control this resource's behavior.
- name
- The unique name of the resulting resource.
- id
- The unique provider ID of the resource to lookup.
- state
- Any extra arguments used during the lookup.
- opts
- A bag of options that control this resource's behavior.
- name
- The unique name of the resulting resource.
- id
- The unique provider ID of the resource to lookup.
- state
- Any extra arguments used during the lookup.
- opts
- A bag of options that control this resource's behavior.
- BigQuery AiFeature Group Big Query 
- 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.
- CreateTime string
- The timestamp of when the FeatureGroup was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- Description string
- The description of the FeatureGroup.
- EffectiveLabels Dictionary<string, string>
- All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
- Etag string
- Used to perform consistent read-modify-write updates.
- Labels Dictionary<string, string>
- 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_labelsfor all of the labels present on the resource.
- Name string
- The resource name of the Feature Group.
- Project string
- The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
- PulumiLabels Dictionary<string, string>
- The combination of labels configured directly on the resource and default labels configured on the provider.
- Region string
- The region of feature group. eg us-central1
- UpdateTime string
- The timestamp of when the FeatureGroup was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- BigQuery AiFeature Group Big Query Args 
- 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.
- CreateTime string
- The timestamp of when the FeatureGroup was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- Description string
- The description of the FeatureGroup.
- EffectiveLabels map[string]string
- All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
- Etag string
- Used to perform consistent read-modify-write updates.
- Labels map[string]string
- 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_labelsfor all of the labels present on the resource.
- Name string
- The resource name of the Feature Group.
- Project string
- The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
- PulumiLabels map[string]string
- The combination of labels configured directly on the resource and default labels configured on the provider.
- Region string
- The region of feature group. eg us-central1
- UpdateTime string
- The timestamp of when the FeatureGroup was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- bigQuery AiFeature Group Big Query 
- 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.
- createTime String
- The timestamp of when the FeatureGroup was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- description String
- The description of the FeatureGroup.
- effectiveLabels Map<String,String>
- All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
- etag String
- Used to perform consistent read-modify-write updates.
- labels Map<String,String>
- 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_labelsfor all of the labels present on the resource.
- name String
- The resource name of the Feature Group.
- project String
- The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
- pulumiLabels Map<String,String>
- The combination of labels configured directly on the resource and default labels configured on the provider.
- region String
- The region of feature group. eg us-central1
- updateTime String
- The timestamp of when the FeatureGroup was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- bigQuery AiFeature Group Big Query 
- 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.
- createTime string
- The timestamp of when the FeatureGroup was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- description string
- The description of the FeatureGroup.
- effectiveLabels {[key: string]: string}
- All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
- etag string
- Used to perform consistent read-modify-write updates.
- labels {[key: string]: string}
- 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_labelsfor all of the labels present on the resource.
- name string
- The resource name of the Feature Group.
- project string
- The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
- pulumiLabels {[key: string]: string}
- The combination of labels configured directly on the resource and default labels configured on the provider.
- region string
- The region of feature group. eg us-central1
- updateTime string
- The timestamp of when the FeatureGroup was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- big_query AiFeature Group Big Query Args 
- 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.
- create_time str
- The timestamp of when the FeatureGroup was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- description str
- The description of the FeatureGroup.
- effective_labels Mapping[str, str]
- All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
- etag str
- Used to perform consistent read-modify-write updates.
- labels Mapping[str, str]
- 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_labelsfor all of the labels present on the resource.
- name str
- The resource name of the Feature Group.
- project str
- The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
- pulumi_labels Mapping[str, str]
- The combination of labels configured directly on the resource and default labels configured on the provider.
- region str
- The region of feature group. eg us-central1
- update_time str
- The timestamp of when the FeatureGroup was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- bigQuery Property Map
- 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.
- createTime String
- The timestamp of when the FeatureGroup was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- description String
- The description of the FeatureGroup.
- effectiveLabels Map<String>
- All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
- etag String
- Used to perform consistent read-modify-write updates.
- labels Map<String>
- 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_labelsfor all of the labels present on the resource.
- name String
- The resource name of the Feature Group.
- project String
- The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
- pulumiLabels Map<String>
- The combination of labels configured directly on the resource and default labels configured on the provider.
- region String
- The region of feature group. eg us-central1
- updateTime String
- The timestamp of when the FeatureGroup was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
Supporting Types
AiFeatureGroupBigQuery, AiFeatureGroupBigQueryArgs          
- BigQuery AiSource Feature Group Big Query Big Query Source 
- The BigQuery source URI that points to either a BigQuery Table or View. Structure is documented below.
- EntityId List<string>Columns 
- Columns to construct entityId / row keys. If not provided defaults to entityId.
- BigQuery AiSource Feature Group Big Query Big Query Source 
- The BigQuery source URI that points to either a BigQuery Table or View. Structure is documented below.
- EntityId []stringColumns 
- Columns to construct entityId / row keys. If not provided defaults to entityId.
- bigQuery AiSource Feature Group Big Query Big Query Source 
- The BigQuery source URI that points to either a BigQuery Table or View. Structure is documented below.
- entityId List<String>Columns 
- Columns to construct entityId / row keys. If not provided defaults to entityId.
- bigQuery AiSource Feature Group Big Query Big Query Source 
- The BigQuery source URI that points to either a BigQuery Table or View. Structure is documented below.
- entityId string[]Columns 
- Columns to construct entityId / row keys. If not provided defaults to entityId.
- big_query_ Aisource Feature Group Big Query Big Query Source 
- The BigQuery source URI that points to either a BigQuery Table or View. Structure is documented below.
- entity_id_ Sequence[str]columns 
- Columns to construct entityId / row keys. If not provided defaults to entityId.
- bigQuery Property MapSource 
- The BigQuery source URI that points to either a BigQuery Table or View. Structure is documented below.
- entityId List<String>Columns 
- Columns to construct entityId / row keys. If not provided defaults to entityId.
AiFeatureGroupBigQueryBigQuerySource, AiFeatureGroupBigQueryBigQuerySourceArgs                
- InputUri string
- BigQuery URI to a table, up to 2000 characters long. For example: bq://projectId.bqDatasetId.bqTableId.
- InputUri string
- BigQuery URI to a table, up to 2000 characters long. For example: bq://projectId.bqDatasetId.bqTableId.
- inputUri String
- BigQuery URI to a table, up to 2000 characters long. For example: bq://projectId.bqDatasetId.bqTableId.
- inputUri string
- BigQuery URI to a table, up to 2000 characters long. For example: bq://projectId.bqDatasetId.bqTableId.
- input_uri str
- BigQuery URI to a table, up to 2000 characters long. For example: bq://projectId.bqDatasetId.bqTableId.
- inputUri String
- BigQuery URI to a table, up to 2000 characters long. For example: bq://projectId.bqDatasetId.bqTableId.
Import
FeatureGroup can be imported using any of these accepted formats:
- projects/{{project}}/locations/{{region}}/featureGroups/{{name}}
- {{project}}/{{region}}/{{name}}
- {{region}}/{{name}}
- {{name}}
When using the pulumi import command, FeatureGroup can be imported using one of the formats above. For example:
$ pulumi import gcp:vertex/aiFeatureGroup:AiFeatureGroup default projects/{{project}}/locations/{{region}}/featureGroups/{{name}}
$ pulumi import gcp:vertex/aiFeatureGroup:AiFeatureGroup default {{project}}/{{region}}/{{name}}
$ pulumi import gcp:vertex/aiFeatureGroup:AiFeatureGroup default {{region}}/{{name}}
$ pulumi import gcp:vertex/aiFeatureGroup:AiFeatureGroup default {{name}}
To learn more about importing existing cloud resources, see Importing resources.
Package Details
- Repository
- Google Cloud (GCP) Classic pulumi/pulumi-gcp
- License
- Apache-2.0
- Notes
- This Pulumi package is based on the google-betaTerraform Provider.