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Google Cloud Classic v7.19.0 published on Thursday, Apr 18, 2024 by Pulumi

gcp.vertex.AiFeatureGroup

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Google Cloud Classic v7.19.0 published on Thursday, Apr 18, 2024 by Pulumi

    Vertex AI Feature Group.

    To get more information about FeatureGroup, see:

    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=gcp.vertex.AiFeatureGroupBigQueryArgs(
            big_query_source=gcp.vertex.AiFeatureGroupBigQueryBigQuerySourceArgs(
                input_uri=pulumi.Output.all(sample_table.project, sample_table.dataset_id, sample_table.table_id).apply(lambda project, dataset_id, table_id: f"bq://{project}.{dataset_id}.{table_id}"),
            ),
            entity_id_columns=["feature_id"],
        ))
    
    package main
    
    import (
    	"fmt"
    
    	"github.com/pulumi/pulumi-gcp/sdk/v7/go/gcp/bigquery"
    	"github.com/pulumi/pulumi-gcp/sdk/v7/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.

    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=gcp.vertex.AiFeatureGroupBigQueryArgs(
            big_query_source=gcp.vertex.AiFeatureGroupBigQueryBigQuerySourceArgs(
                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

    The AiFeatureGroup resource accepts the following input properties:

    BigQuery AiFeatureGroupBigQuery
    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_labels for 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 AiFeatureGroupBigQueryArgs
    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_labels for 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 AiFeatureGroupBigQuery
    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_labels for 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 AiFeatureGroupBigQuery
    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_labels for 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 AiFeatureGroupBigQueryArgs
    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_labels for 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_labels for 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) -> AiFeatureGroup
    func 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)
    Resource lookup is not supported in YAML
    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.
    The following state arguments are supported:
    BigQuery AiFeatureGroupBigQuery
    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_labels for 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 AiFeatureGroupBigQueryArgs
    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_labels for 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 AiFeatureGroupBigQuery
    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_labels for 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 AiFeatureGroupBigQuery
    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_labels for 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 AiFeatureGroupBigQueryArgs
    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_labels for 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_labels for 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

    BigQuerySource AiFeatureGroupBigQueryBigQuerySource
    The BigQuery source URI that points to either a BigQuery Table or View. Structure is documented below.
    EntityIdColumns List<string>
    Columns to construct entityId / row keys. Currently only supports 1 entity_id_column. If not provided defaults to entityId.
    BigQuerySource AiFeatureGroupBigQueryBigQuerySource
    The BigQuery source URI that points to either a BigQuery Table or View. Structure is documented below.
    EntityIdColumns []string
    Columns to construct entityId / row keys. Currently only supports 1 entity_id_column. If not provided defaults to entityId.
    bigQuerySource AiFeatureGroupBigQueryBigQuerySource
    The BigQuery source URI that points to either a BigQuery Table or View. Structure is documented below.
    entityIdColumns List<String>
    Columns to construct entityId / row keys. Currently only supports 1 entity_id_column. If not provided defaults to entityId.
    bigQuerySource AiFeatureGroupBigQueryBigQuerySource
    The BigQuery source URI that points to either a BigQuery Table or View. Structure is documented below.
    entityIdColumns string[]
    Columns to construct entityId / row keys. Currently only supports 1 entity_id_column. If not provided defaults to entityId.
    big_query_source AiFeatureGroupBigQueryBigQuerySource
    The BigQuery source URI that points to either a BigQuery Table or View. Structure is documented below.
    entity_id_columns Sequence[str]
    Columns to construct entityId / row keys. Currently only supports 1 entity_id_column. If not provided defaults to entityId.
    bigQuerySource Property Map
    The BigQuery source URI that points to either a BigQuery Table or View. Structure is documented below.
    entityIdColumns List<String>
    Columns to construct entityId / row keys. Currently only supports 1 entity_id_column. 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-beta Terraform Provider.
    gcp logo
    Google Cloud Classic v7.19.0 published on Thursday, Apr 18, 2024 by Pulumi