pulumi-gcp-kotlin/com.pulumi.gcp.vertex.kotlin/AiFeatureGroupFeatureArgs

AiFeatureGroupFeatureArgs

data class AiFeatureGroupFeatureArgs(val description: Output<String>? = null, val featureGroup: Output<String>? = null, val labels: Output<Map<String, String>>? = null, val name: Output<String>? = null, val project: Output<String>? = null, val region: Output<String>? = null, val versionColumnName: Output<String>? = null) : ConvertibleToJava<AiFeatureGroupFeatureArgs>

Vertex AI Feature Group Feature is feature metadata information. To get more information about FeatureGroupFeature, see:

Example Usage

Vertex Ai Feature Group Feature

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": "example_feature",
        "type": "STRING",
        "mode": "NULLABLE"
    },
    {
        "name": "feature_timestamp",
        "type": "TIMESTAMP",
        "mode": "NULLABLE"
    }
]
`,
});
const sampleFeatureGroup = new gcp.vertex.AiFeatureGroup("sample_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"],
    },
});
const featureGroupFeature = new gcp.vertex.AiFeatureGroupFeature("feature_group_feature", {
    name: "example_feature",
    region: "us-central1",
    featureGroup: sampleFeatureGroup.name,
    description: "A sample feature",
    labels: {
        "label-one": "value-one",
    },
});
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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": "example_feature",
        "type": "STRING",
        "mode": "NULLABLE"
    },
    {
        "name": "feature_timestamp",
        "type": "TIMESTAMP",
        "mode": "NULLABLE"
    }
]
""")
sample_feature_group = gcp.vertex.AiFeatureGroup("sample_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']}&#46;{resolved_outputs['dataset_id']}&#46;{resolved_outputs['table_id']}")
,
        },
        "entity_id_columns": ["feature_id"],
    })
feature_group_feature = gcp.vertex.AiFeatureGroupFeature("feature_group_feature",
    name="example_feature",
    region="us-central1",
    feature_group=sample_feature_group.name,
    description="A sample feature",
    labels={
        "label-one": "value-one",
    })
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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"": ""example_feature"",
        ""type"": ""STRING"",
        ""mode"": ""NULLABLE""
    },
    {
        ""name"": ""feature_timestamp"",
        ""type"": ""TIMESTAMP"",
        ""mode"": ""NULLABLE""
    }
]
",
    });
    var sampleFeatureGroup = new Gcp.Vertex.AiFeatureGroup("sample_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",
            },
        },
    });
    var featureGroupFeature = new Gcp.Vertex.AiFeatureGroupFeature("feature_group_feature", new()
    {
        Name = "example_feature",
        Region = "us-central1",
        FeatureGroup = sampleFeatureGroup.Name,
        Description = "A sample feature",
        Labels =
        {
            { "label-one", "value-one" },
        },
    });
});
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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": "example_feature",
        "type": "STRING",
        "mode": "NULLABLE"
    },
    {
        "name": "feature_timestamp",
        "type": "TIMESTAMP",
        "mode": "NULLABLE"
    }
]
`),
		})
		if err != nil {
			return err
		}
		sampleFeatureGroup, err := vertex.NewAiFeatureGroup(ctx, "sample_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
		}
		_, err = vertex.NewAiFeatureGroupFeature(ctx, "feature_group_feature", &vertex.AiFeatureGroupFeatureArgs{
			Name:         pulumi.String("example_feature"),
			Region:       pulumi.String("us-central1"),
			FeatureGroup: sampleFeatureGroup.Name,
			Description:  pulumi.String("A sample feature"),
			Labels: pulumi.StringMap{
				"label-one": pulumi.String("value-one"),
			},
		})
		if err != nil {
			return err
		}
		return nil
	})
}
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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 com.pulumi.gcp.vertex.AiFeatureGroupFeature;
import com.pulumi.gcp.vertex.AiFeatureGroupFeatureArgs;
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": "example_feature",
        "type": "STRING",
        "mode": "NULLABLE"
    },
    {
        "name": "feature_timestamp",
        "type": "TIMESTAMP",
        "mode": "NULLABLE"
    }
]
            """)
            .build());
        var sampleFeatureGroup = new AiFeatureGroup("sampleFeatureGroup", 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());
        var featureGroupFeature = new AiFeatureGroupFeature("featureGroupFeature", AiFeatureGroupFeatureArgs.builder()
            .name("example_feature")
            .region("us-central1")
            .featureGroup(sampleFeatureGroup.name())
            .description("A sample feature")
            .labels(Map.of("label-one", "value-one"))
            .build());
    }
}
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resources:
  featureGroupFeature:
    type: gcp:vertex:AiFeatureGroupFeature
    name: feature_group_feature
    properties:
      name: example_feature
      region: us-central1
      featureGroup: ${sampleFeatureGroup.name}
      description: A sample feature
      labels:
        label-one: value-one
  sampleFeatureGroup:
    type: gcp:vertex:AiFeatureGroup
    name: sample_feature_group
    properties:
      name: example_feature_group
      description: A sample feature group
      region: us-central1
      labels:
        label-one: value-one
      bigQuery:
        bigQuerySource:
          inputUri: bq://${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": "example_feature",
                "type": "STRING",
                "mode": "NULLABLE"
            },
            {
                "name": "feature_timestamp",
                "type": "TIMESTAMP",
                "mode": "NULLABLE"
            }
        ]
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Import

FeatureGroupFeature can be imported using any of these accepted formats:

  • projects/{{project}}/locations/{{region}}/featureGroups/{{feature_group}}/features/{{name}}

  • {{project}}/{{region}}/{{feature_group}}/{{name}}

  • {{region}}/{{feature_group}}/{{name}}

  • {{feature_group}}/{{name}} When using the pulumi import command, FeatureGroupFeature can be imported using one of the formats above. For example:

$ pulumi import gcp:vertex/aiFeatureGroupFeature:AiFeatureGroupFeature default projects/{{project}}/locations/{{region}}/featureGroups/{{feature_group}}/features/{{name}}
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$ pulumi import gcp:vertex/aiFeatureGroupFeature:AiFeatureGroupFeature default {{project}}/{{region}}/{{feature_group}}/{{name}}
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$ pulumi import gcp:vertex/aiFeatureGroupFeature:AiFeatureGroupFeature default {{region}}/{{feature_group}}/{{name}}
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$ pulumi import gcp:vertex/aiFeatureGroupFeature:AiFeatureGroupFeature default {{feature_group}}/{{name}}
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Constructors

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constructor(description: Output<String>? = null, featureGroup: Output<String>? = null, labels: Output<Map<String, String>>? = null, name: Output<String>? = null, project: Output<String>? = null, region: Output<String>? = null, versionColumnName: Output<String>? = null)

Properties

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val description: Output<String>? = null

The description of the FeatureGroup.

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val featureGroup: Output<String>? = null

The name of the Feature Group.

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val labels: Output<Map<String, String>>? = null

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.

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val name: Output<String>? = null

The resource name of the Feature Group Feature.

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val project: Output<String>? = null

The ID of the project in which the resource belongs. If it is not provided, the provider project is used.

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val region: Output<String>? = null

The region for the resource. It should be the same as the feature group's region.

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val versionColumnName: Output<String>? = null

The name of the BigQuery Table/View column hosting data for this version. If no value is provided, will use featureId.

Functions

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open override fun toJava(): AiFeatureGroupFeatureArgs