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  4. dataplex
  5. Datascan
Google Cloud Classic v7.27.0 published on Thursday, Jun 13, 2024 by Pulumi

gcp.dataplex.Datascan

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Google Cloud Classic v7.27.0 published on Thursday, Jun 13, 2024 by Pulumi

    Represents a user-visible job which provides the insights for the related data source.

    To get more information about Datascan, see:

    Example Usage

    Dataplex Datascan Basic Profile

    import * as pulumi from "@pulumi/pulumi";
    import * as gcp from "@pulumi/gcp";
    
    const basicProfile = new gcp.dataplex.Datascan("basic_profile", {
        location: "us-central1",
        dataScanId: "dataprofile-basic",
        data: {
            resource: "//bigquery.googleapis.com/projects/bigquery-public-data/datasets/samples/tables/shakespeare",
        },
        executionSpec: {
            trigger: {
                onDemand: {},
            },
        },
        dataProfileSpec: {},
        project: "my-project-name",
    });
    
    import pulumi
    import pulumi_gcp as gcp
    
    basic_profile = gcp.dataplex.Datascan("basic_profile",
        location="us-central1",
        data_scan_id="dataprofile-basic",
        data=gcp.dataplex.DatascanDataArgs(
            resource="//bigquery.googleapis.com/projects/bigquery-public-data/datasets/samples/tables/shakespeare",
        ),
        execution_spec=gcp.dataplex.DatascanExecutionSpecArgs(
            trigger=gcp.dataplex.DatascanExecutionSpecTriggerArgs(
                on_demand=gcp.dataplex.DatascanExecutionSpecTriggerOnDemandArgs(),
            ),
        ),
        data_profile_spec=gcp.dataplex.DatascanDataProfileSpecArgs(),
        project="my-project-name")
    
    package main
    
    import (
    	"github.com/pulumi/pulumi-gcp/sdk/v7/go/gcp/dataplex"
    	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
    )
    
    func main() {
    	pulumi.Run(func(ctx *pulumi.Context) error {
    		_, err := dataplex.NewDatascan(ctx, "basic_profile", &dataplex.DatascanArgs{
    			Location:   pulumi.String("us-central1"),
    			DataScanId: pulumi.String("dataprofile-basic"),
    			Data: &dataplex.DatascanDataArgs{
    				Resource: pulumi.String("//bigquery.googleapis.com/projects/bigquery-public-data/datasets/samples/tables/shakespeare"),
    			},
    			ExecutionSpec: &dataplex.DatascanExecutionSpecArgs{
    				Trigger: &dataplex.DatascanExecutionSpecTriggerArgs{
    					OnDemand: nil,
    				},
    			},
    			DataProfileSpec: nil,
    			Project:         pulumi.String("my-project-name"),
    		})
    		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 basicProfile = new Gcp.DataPlex.Datascan("basic_profile", new()
        {
            Location = "us-central1",
            DataScanId = "dataprofile-basic",
            Data = new Gcp.DataPlex.Inputs.DatascanDataArgs
            {
                Resource = "//bigquery.googleapis.com/projects/bigquery-public-data/datasets/samples/tables/shakespeare",
            },
            ExecutionSpec = new Gcp.DataPlex.Inputs.DatascanExecutionSpecArgs
            {
                Trigger = new Gcp.DataPlex.Inputs.DatascanExecutionSpecTriggerArgs
                {
                    OnDemand = null,
                },
            },
            DataProfileSpec = null,
            Project = "my-project-name",
        });
    
    });
    
    package generated_program;
    
    import com.pulumi.Context;
    import com.pulumi.Pulumi;
    import com.pulumi.core.Output;
    import com.pulumi.gcp.dataplex.Datascan;
    import com.pulumi.gcp.dataplex.DatascanArgs;
    import com.pulumi.gcp.dataplex.inputs.DatascanDataArgs;
    import com.pulumi.gcp.dataplex.inputs.DatascanExecutionSpecArgs;
    import com.pulumi.gcp.dataplex.inputs.DatascanExecutionSpecTriggerArgs;
    import com.pulumi.gcp.dataplex.inputs.DatascanExecutionSpecTriggerOnDemandArgs;
    import com.pulumi.gcp.dataplex.inputs.DatascanDataProfileSpecArgs;
    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 basicProfile = new Datascan("basicProfile", DatascanArgs.builder()
                .location("us-central1")
                .dataScanId("dataprofile-basic")
                .data(DatascanDataArgs.builder()
                    .resource("//bigquery.googleapis.com/projects/bigquery-public-data/datasets/samples/tables/shakespeare")
                    .build())
                .executionSpec(DatascanExecutionSpecArgs.builder()
                    .trigger(DatascanExecutionSpecTriggerArgs.builder()
                        .onDemand()
                        .build())
                    .build())
                .dataProfileSpec()
                .project("my-project-name")
                .build());
    
        }
    }
    
    resources:
      basicProfile:
        type: gcp:dataplex:Datascan
        name: basic_profile
        properties:
          location: us-central1
          dataScanId: dataprofile-basic
          data:
            resource: //bigquery.googleapis.com/projects/bigquery-public-data/datasets/samples/tables/shakespeare
          executionSpec:
            trigger:
              onDemand: {}
          dataProfileSpec: {}
          project: my-project-name
    

    Dataplex Datascan Full Profile

    import * as pulumi from "@pulumi/pulumi";
    import * as gcp from "@pulumi/gcp";
    
    const source = new gcp.bigquery.Dataset("source", {
        datasetId: "dataplex_dataset",
        friendlyName: "test",
        description: "This is a test description",
        location: "US",
        deleteContentsOnDestroy: true,
    });
    const fullProfile = new gcp.dataplex.Datascan("full_profile", {
        location: "us-central1",
        displayName: "Full Datascan Profile",
        dataScanId: "dataprofile-full",
        description: "Example resource - Full Datascan Profile",
        labels: {
            author: "billing",
        },
        data: {
            resource: "//bigquery.googleapis.com/projects/bigquery-public-data/datasets/samples/tables/shakespeare",
        },
        executionSpec: {
            trigger: {
                schedule: {
                    cron: "TZ=America/New_York 1 1 * * *",
                },
            },
        },
        dataProfileSpec: {
            samplingPercent: 80,
            rowFilter: "word_count > 10",
            includeFields: {
                fieldNames: ["word_count"],
            },
            excludeFields: {
                fieldNames: ["property_type"],
            },
            postScanActions: {
                bigqueryExport: {
                    resultsTable: "//bigquery.googleapis.com/projects/my-project-name/datasets/dataplex_dataset/tables/profile_export",
                },
            },
        },
        project: "my-project-name",
    }, {
        dependsOn: [source],
    });
    
    import pulumi
    import pulumi_gcp as gcp
    
    source = gcp.bigquery.Dataset("source",
        dataset_id="dataplex_dataset",
        friendly_name="test",
        description="This is a test description",
        location="US",
        delete_contents_on_destroy=True)
    full_profile = gcp.dataplex.Datascan("full_profile",
        location="us-central1",
        display_name="Full Datascan Profile",
        data_scan_id="dataprofile-full",
        description="Example resource - Full Datascan Profile",
        labels={
            "author": "billing",
        },
        data=gcp.dataplex.DatascanDataArgs(
            resource="//bigquery.googleapis.com/projects/bigquery-public-data/datasets/samples/tables/shakespeare",
        ),
        execution_spec=gcp.dataplex.DatascanExecutionSpecArgs(
            trigger=gcp.dataplex.DatascanExecutionSpecTriggerArgs(
                schedule=gcp.dataplex.DatascanExecutionSpecTriggerScheduleArgs(
                    cron="TZ=America/New_York 1 1 * * *",
                ),
            ),
        ),
        data_profile_spec=gcp.dataplex.DatascanDataProfileSpecArgs(
            sampling_percent=80,
            row_filter="word_count > 10",
            include_fields=gcp.dataplex.DatascanDataProfileSpecIncludeFieldsArgs(
                field_names=["word_count"],
            ),
            exclude_fields=gcp.dataplex.DatascanDataProfileSpecExcludeFieldsArgs(
                field_names=["property_type"],
            ),
            post_scan_actions=gcp.dataplex.DatascanDataProfileSpecPostScanActionsArgs(
                bigquery_export=gcp.dataplex.DatascanDataProfileSpecPostScanActionsBigqueryExportArgs(
                    results_table="//bigquery.googleapis.com/projects/my-project-name/datasets/dataplex_dataset/tables/profile_export",
                ),
            ),
        ),
        project="my-project-name",
        opts=pulumi.ResourceOptions(depends_on=[source]))
    
    package main
    
    import (
    	"github.com/pulumi/pulumi-gcp/sdk/v7/go/gcp/bigquery"
    	"github.com/pulumi/pulumi-gcp/sdk/v7/go/gcp/dataplex"
    	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
    )
    
    func main() {
    	pulumi.Run(func(ctx *pulumi.Context) error {
    		source, err := bigquery.NewDataset(ctx, "source", &bigquery.DatasetArgs{
    			DatasetId:               pulumi.String("dataplex_dataset"),
    			FriendlyName:            pulumi.String("test"),
    			Description:             pulumi.String("This is a test description"),
    			Location:                pulumi.String("US"),
    			DeleteContentsOnDestroy: pulumi.Bool(true),
    		})
    		if err != nil {
    			return err
    		}
    		_, err = dataplex.NewDatascan(ctx, "full_profile", &dataplex.DatascanArgs{
    			Location:    pulumi.String("us-central1"),
    			DisplayName: pulumi.String("Full Datascan Profile"),
    			DataScanId:  pulumi.String("dataprofile-full"),
    			Description: pulumi.String("Example resource - Full Datascan Profile"),
    			Labels: pulumi.StringMap{
    				"author": pulumi.String("billing"),
    			},
    			Data: &dataplex.DatascanDataArgs{
    				Resource: pulumi.String("//bigquery.googleapis.com/projects/bigquery-public-data/datasets/samples/tables/shakespeare"),
    			},
    			ExecutionSpec: &dataplex.DatascanExecutionSpecArgs{
    				Trigger: &dataplex.DatascanExecutionSpecTriggerArgs{
    					Schedule: &dataplex.DatascanExecutionSpecTriggerScheduleArgs{
    						Cron: pulumi.String("TZ=America/New_York 1 1 * * *"),
    					},
    				},
    			},
    			DataProfileSpec: &dataplex.DatascanDataProfileSpecArgs{
    				SamplingPercent: pulumi.Float64(80),
    				RowFilter:       pulumi.String("word_count > 10"),
    				IncludeFields: &dataplex.DatascanDataProfileSpecIncludeFieldsArgs{
    					FieldNames: pulumi.StringArray{
    						pulumi.String("word_count"),
    					},
    				},
    				ExcludeFields: &dataplex.DatascanDataProfileSpecExcludeFieldsArgs{
    					FieldNames: pulumi.StringArray{
    						pulumi.String("property_type"),
    					},
    				},
    				PostScanActions: &dataplex.DatascanDataProfileSpecPostScanActionsArgs{
    					BigqueryExport: &dataplex.DatascanDataProfileSpecPostScanActionsBigqueryExportArgs{
    						ResultsTable: pulumi.String("//bigquery.googleapis.com/projects/my-project-name/datasets/dataplex_dataset/tables/profile_export"),
    					},
    				},
    			},
    			Project: pulumi.String("my-project-name"),
    		}, pulumi.DependsOn([]pulumi.Resource{
    			source,
    		}))
    		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 source = new Gcp.BigQuery.Dataset("source", new()
        {
            DatasetId = "dataplex_dataset",
            FriendlyName = "test",
            Description = "This is a test description",
            Location = "US",
            DeleteContentsOnDestroy = true,
        });
    
        var fullProfile = new Gcp.DataPlex.Datascan("full_profile", new()
        {
            Location = "us-central1",
            DisplayName = "Full Datascan Profile",
            DataScanId = "dataprofile-full",
            Description = "Example resource - Full Datascan Profile",
            Labels = 
            {
                { "author", "billing" },
            },
            Data = new Gcp.DataPlex.Inputs.DatascanDataArgs
            {
                Resource = "//bigquery.googleapis.com/projects/bigquery-public-data/datasets/samples/tables/shakespeare",
            },
            ExecutionSpec = new Gcp.DataPlex.Inputs.DatascanExecutionSpecArgs
            {
                Trigger = new Gcp.DataPlex.Inputs.DatascanExecutionSpecTriggerArgs
                {
                    Schedule = new Gcp.DataPlex.Inputs.DatascanExecutionSpecTriggerScheduleArgs
                    {
                        Cron = "TZ=America/New_York 1 1 * * *",
                    },
                },
            },
            DataProfileSpec = new Gcp.DataPlex.Inputs.DatascanDataProfileSpecArgs
            {
                SamplingPercent = 80,
                RowFilter = "word_count > 10",
                IncludeFields = new Gcp.DataPlex.Inputs.DatascanDataProfileSpecIncludeFieldsArgs
                {
                    FieldNames = new[]
                    {
                        "word_count",
                    },
                },
                ExcludeFields = new Gcp.DataPlex.Inputs.DatascanDataProfileSpecExcludeFieldsArgs
                {
                    FieldNames = new[]
                    {
                        "property_type",
                    },
                },
                PostScanActions = new Gcp.DataPlex.Inputs.DatascanDataProfileSpecPostScanActionsArgs
                {
                    BigqueryExport = new Gcp.DataPlex.Inputs.DatascanDataProfileSpecPostScanActionsBigqueryExportArgs
                    {
                        ResultsTable = "//bigquery.googleapis.com/projects/my-project-name/datasets/dataplex_dataset/tables/profile_export",
                    },
                },
            },
            Project = "my-project-name",
        }, new CustomResourceOptions
        {
            DependsOn =
            {
                source,
            },
        });
    
    });
    
    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.dataplex.Datascan;
    import com.pulumi.gcp.dataplex.DatascanArgs;
    import com.pulumi.gcp.dataplex.inputs.DatascanDataArgs;
    import com.pulumi.gcp.dataplex.inputs.DatascanExecutionSpecArgs;
    import com.pulumi.gcp.dataplex.inputs.DatascanExecutionSpecTriggerArgs;
    import com.pulumi.gcp.dataplex.inputs.DatascanExecutionSpecTriggerScheduleArgs;
    import com.pulumi.gcp.dataplex.inputs.DatascanDataProfileSpecArgs;
    import com.pulumi.gcp.dataplex.inputs.DatascanDataProfileSpecIncludeFieldsArgs;
    import com.pulumi.gcp.dataplex.inputs.DatascanDataProfileSpecExcludeFieldsArgs;
    import com.pulumi.gcp.dataplex.inputs.DatascanDataProfileSpecPostScanActionsArgs;
    import com.pulumi.gcp.dataplex.inputs.DatascanDataProfileSpecPostScanActionsBigqueryExportArgs;
    import com.pulumi.resources.CustomResourceOptions;
    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 source = new Dataset("source", DatasetArgs.builder()
                .datasetId("dataplex_dataset")
                .friendlyName("test")
                .description("This is a test description")
                .location("US")
                .deleteContentsOnDestroy(true)
                .build());
    
            var fullProfile = new Datascan("fullProfile", DatascanArgs.builder()
                .location("us-central1")
                .displayName("Full Datascan Profile")
                .dataScanId("dataprofile-full")
                .description("Example resource - Full Datascan Profile")
                .labels(Map.of("author", "billing"))
                .data(DatascanDataArgs.builder()
                    .resource("//bigquery.googleapis.com/projects/bigquery-public-data/datasets/samples/tables/shakespeare")
                    .build())
                .executionSpec(DatascanExecutionSpecArgs.builder()
                    .trigger(DatascanExecutionSpecTriggerArgs.builder()
                        .schedule(DatascanExecutionSpecTriggerScheduleArgs.builder()
                            .cron("TZ=America/New_York 1 1 * * *")
                            .build())
                        .build())
                    .build())
                .dataProfileSpec(DatascanDataProfileSpecArgs.builder()
                    .samplingPercent(80)
                    .rowFilter("word_count > 10")
                    .includeFields(DatascanDataProfileSpecIncludeFieldsArgs.builder()
                        .fieldNames("word_count")
                        .build())
                    .excludeFields(DatascanDataProfileSpecExcludeFieldsArgs.builder()
                        .fieldNames("property_type")
                        .build())
                    .postScanActions(DatascanDataProfileSpecPostScanActionsArgs.builder()
                        .bigqueryExport(DatascanDataProfileSpecPostScanActionsBigqueryExportArgs.builder()
                            .resultsTable("//bigquery.googleapis.com/projects/my-project-name/datasets/dataplex_dataset/tables/profile_export")
                            .build())
                        .build())
                    .build())
                .project("my-project-name")
                .build(), CustomResourceOptions.builder()
                    .dependsOn(source)
                    .build());
    
        }
    }
    
    resources:
      fullProfile:
        type: gcp:dataplex:Datascan
        name: full_profile
        properties:
          location: us-central1
          displayName: Full Datascan Profile
          dataScanId: dataprofile-full
          description: Example resource - Full Datascan Profile
          labels:
            author: billing
          data:
            resource: //bigquery.googleapis.com/projects/bigquery-public-data/datasets/samples/tables/shakespeare
          executionSpec:
            trigger:
              schedule:
                cron: TZ=America/New_York 1 1 * * *
          dataProfileSpec:
            samplingPercent: 80
            rowFilter: word_count > 10
            includeFields:
              fieldNames:
                - word_count
            excludeFields:
              fieldNames:
                - property_type
            postScanActions:
              bigqueryExport:
                resultsTable: //bigquery.googleapis.com/projects/my-project-name/datasets/dataplex_dataset/tables/profile_export
          project: my-project-name
        options:
          dependson:
            - ${source}
      source:
        type: gcp:bigquery:Dataset
        properties:
          datasetId: dataplex_dataset
          friendlyName: test
          description: This is a test description
          location: US
          deleteContentsOnDestroy: true
    

    Dataplex Datascan Basic Quality

    import * as pulumi from "@pulumi/pulumi";
    import * as gcp from "@pulumi/gcp";
    
    const basicQuality = new gcp.dataplex.Datascan("basic_quality", {
        location: "us-central1",
        dataScanId: "dataquality-basic",
        data: {
            resource: "//bigquery.googleapis.com/projects/bigquery-public-data/datasets/samples/tables/shakespeare",
        },
        executionSpec: {
            trigger: {
                onDemand: {},
            },
        },
        dataQualitySpec: {
            rules: [{
                dimension: "VALIDITY",
                name: "rule1",
                description: "rule 1 for validity dimension",
                tableConditionExpectation: {
                    sqlExpression: "COUNT(*) > 0",
                },
            }],
        },
        project: "my-project-name",
    });
    
    import pulumi
    import pulumi_gcp as gcp
    
    basic_quality = gcp.dataplex.Datascan("basic_quality",
        location="us-central1",
        data_scan_id="dataquality-basic",
        data=gcp.dataplex.DatascanDataArgs(
            resource="//bigquery.googleapis.com/projects/bigquery-public-data/datasets/samples/tables/shakespeare",
        ),
        execution_spec=gcp.dataplex.DatascanExecutionSpecArgs(
            trigger=gcp.dataplex.DatascanExecutionSpecTriggerArgs(
                on_demand=gcp.dataplex.DatascanExecutionSpecTriggerOnDemandArgs(),
            ),
        ),
        data_quality_spec=gcp.dataplex.DatascanDataQualitySpecArgs(
            rules=[gcp.dataplex.DatascanDataQualitySpecRuleArgs(
                dimension="VALIDITY",
                name="rule1",
                description="rule 1 for validity dimension",
                table_condition_expectation=gcp.dataplex.DatascanDataQualitySpecRuleTableConditionExpectationArgs(
                    sql_expression="COUNT(*) > 0",
                ),
            )],
        ),
        project="my-project-name")
    
    package main
    
    import (
    	"github.com/pulumi/pulumi-gcp/sdk/v7/go/gcp/dataplex"
    	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
    )
    
    func main() {
    	pulumi.Run(func(ctx *pulumi.Context) error {
    		_, err := dataplex.NewDatascan(ctx, "basic_quality", &dataplex.DatascanArgs{
    			Location:   pulumi.String("us-central1"),
    			DataScanId: pulumi.String("dataquality-basic"),
    			Data: &dataplex.DatascanDataArgs{
    				Resource: pulumi.String("//bigquery.googleapis.com/projects/bigquery-public-data/datasets/samples/tables/shakespeare"),
    			},
    			ExecutionSpec: &dataplex.DatascanExecutionSpecArgs{
    				Trigger: &dataplex.DatascanExecutionSpecTriggerArgs{
    					OnDemand: nil,
    				},
    			},
    			DataQualitySpec: &dataplex.DatascanDataQualitySpecArgs{
    				Rules: dataplex.DatascanDataQualitySpecRuleArray{
    					&dataplex.DatascanDataQualitySpecRuleArgs{
    						Dimension:   pulumi.String("VALIDITY"),
    						Name:        pulumi.String("rule1"),
    						Description: pulumi.String("rule 1 for validity dimension"),
    						TableConditionExpectation: &dataplex.DatascanDataQualitySpecRuleTableConditionExpectationArgs{
    							SqlExpression: pulumi.String("COUNT(*) > 0"),
    						},
    					},
    				},
    			},
    			Project: pulumi.String("my-project-name"),
    		})
    		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 basicQuality = new Gcp.DataPlex.Datascan("basic_quality", new()
        {
            Location = "us-central1",
            DataScanId = "dataquality-basic",
            Data = new Gcp.DataPlex.Inputs.DatascanDataArgs
            {
                Resource = "//bigquery.googleapis.com/projects/bigquery-public-data/datasets/samples/tables/shakespeare",
            },
            ExecutionSpec = new Gcp.DataPlex.Inputs.DatascanExecutionSpecArgs
            {
                Trigger = new Gcp.DataPlex.Inputs.DatascanExecutionSpecTriggerArgs
                {
                    OnDemand = null,
                },
            },
            DataQualitySpec = new Gcp.DataPlex.Inputs.DatascanDataQualitySpecArgs
            {
                Rules = new[]
                {
                    new Gcp.DataPlex.Inputs.DatascanDataQualitySpecRuleArgs
                    {
                        Dimension = "VALIDITY",
                        Name = "rule1",
                        Description = "rule 1 for validity dimension",
                        TableConditionExpectation = new Gcp.DataPlex.Inputs.DatascanDataQualitySpecRuleTableConditionExpectationArgs
                        {
                            SqlExpression = "COUNT(*) > 0",
                        },
                    },
                },
            },
            Project = "my-project-name",
        });
    
    });
    
    package generated_program;
    
    import com.pulumi.Context;
    import com.pulumi.Pulumi;
    import com.pulumi.core.Output;
    import com.pulumi.gcp.dataplex.Datascan;
    import com.pulumi.gcp.dataplex.DatascanArgs;
    import com.pulumi.gcp.dataplex.inputs.DatascanDataArgs;
    import com.pulumi.gcp.dataplex.inputs.DatascanExecutionSpecArgs;
    import com.pulumi.gcp.dataplex.inputs.DatascanExecutionSpecTriggerArgs;
    import com.pulumi.gcp.dataplex.inputs.DatascanExecutionSpecTriggerOnDemandArgs;
    import com.pulumi.gcp.dataplex.inputs.DatascanDataQualitySpecArgs;
    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 basicQuality = new Datascan("basicQuality", DatascanArgs.builder()
                .location("us-central1")
                .dataScanId("dataquality-basic")
                .data(DatascanDataArgs.builder()
                    .resource("//bigquery.googleapis.com/projects/bigquery-public-data/datasets/samples/tables/shakespeare")
                    .build())
                .executionSpec(DatascanExecutionSpecArgs.builder()
                    .trigger(DatascanExecutionSpecTriggerArgs.builder()
                        .onDemand()
                        .build())
                    .build())
                .dataQualitySpec(DatascanDataQualitySpecArgs.builder()
                    .rules(DatascanDataQualitySpecRuleArgs.builder()
                        .dimension("VALIDITY")
                        .name("rule1")
                        .description("rule 1 for validity dimension")
                        .tableConditionExpectation(DatascanDataQualitySpecRuleTableConditionExpectationArgs.builder()
                            .sqlExpression("COUNT(*) > 0")
                            .build())
                        .build())
                    .build())
                .project("my-project-name")
                .build());
    
        }
    }
    
    resources:
      basicQuality:
        type: gcp:dataplex:Datascan
        name: basic_quality
        properties:
          location: us-central1
          dataScanId: dataquality-basic
          data:
            resource: //bigquery.googleapis.com/projects/bigquery-public-data/datasets/samples/tables/shakespeare
          executionSpec:
            trigger:
              onDemand: {}
          dataQualitySpec:
            rules:
              - dimension: VALIDITY
                name: rule1
                description: rule 1 for validity dimension
                tableConditionExpectation:
                  sqlExpression: COUNT(*) > 0
          project: my-project-name
    

    Dataplex Datascan Full Quality

    import * as pulumi from "@pulumi/pulumi";
    import * as gcp from "@pulumi/gcp";
    
    const fullQuality = new gcp.dataplex.Datascan("full_quality", {
        location: "us-central1",
        displayName: "Full Datascan Quality",
        dataScanId: "dataquality-full",
        description: "Example resource - Full Datascan Quality",
        labels: {
            author: "billing",
        },
        data: {
            resource: "//bigquery.googleapis.com/projects/bigquery-public-data/datasets/austin_bikeshare/tables/bikeshare_stations",
        },
        executionSpec: {
            trigger: {
                schedule: {
                    cron: "TZ=America/New_York 1 1 * * *",
                },
            },
            field: "modified_date",
        },
        dataQualitySpec: {
            samplingPercent: 5,
            rowFilter: "station_id > 1000",
            rules: [
                {
                    column: "address",
                    dimension: "VALIDITY",
                    threshold: 0.99,
                    nonNullExpectation: {},
                },
                {
                    column: "council_district",
                    dimension: "VALIDITY",
                    ignoreNull: true,
                    threshold: 0.9,
                    rangeExpectation: {
                        minValue: "1",
                        maxValue: "10",
                        strictMinEnabled: true,
                        strictMaxEnabled: false,
                    },
                },
                {
                    column: "power_type",
                    dimension: "VALIDITY",
                    ignoreNull: false,
                    regexExpectation: {
                        regex: ".*solar.*",
                    },
                },
                {
                    column: "property_type",
                    dimension: "VALIDITY",
                    ignoreNull: false,
                    setExpectation: {
                        values: [
                            "sidewalk",
                            "parkland",
                        ],
                    },
                },
                {
                    column: "address",
                    dimension: "UNIQUENESS",
                    uniquenessExpectation: {},
                },
                {
                    column: "number_of_docks",
                    dimension: "VALIDITY",
                    statisticRangeExpectation: {
                        statistic: "MEAN",
                        minValue: "5",
                        maxValue: "15",
                        strictMinEnabled: true,
                        strictMaxEnabled: true,
                    },
                },
                {
                    column: "footprint_length",
                    dimension: "VALIDITY",
                    rowConditionExpectation: {
                        sqlExpression: "footprint_length > 0 AND footprint_length <= 10",
                    },
                },
                {
                    dimension: "VALIDITY",
                    tableConditionExpectation: {
                        sqlExpression: "COUNT(*) > 0",
                    },
                },
            ],
        },
        project: "my-project-name",
    });
    
    import pulumi
    import pulumi_gcp as gcp
    
    full_quality = gcp.dataplex.Datascan("full_quality",
        location="us-central1",
        display_name="Full Datascan Quality",
        data_scan_id="dataquality-full",
        description="Example resource - Full Datascan Quality",
        labels={
            "author": "billing",
        },
        data=gcp.dataplex.DatascanDataArgs(
            resource="//bigquery.googleapis.com/projects/bigquery-public-data/datasets/austin_bikeshare/tables/bikeshare_stations",
        ),
        execution_spec=gcp.dataplex.DatascanExecutionSpecArgs(
            trigger=gcp.dataplex.DatascanExecutionSpecTriggerArgs(
                schedule=gcp.dataplex.DatascanExecutionSpecTriggerScheduleArgs(
                    cron="TZ=America/New_York 1 1 * * *",
                ),
            ),
            field="modified_date",
        ),
        data_quality_spec=gcp.dataplex.DatascanDataQualitySpecArgs(
            sampling_percent=5,
            row_filter="station_id > 1000",
            rules=[
                gcp.dataplex.DatascanDataQualitySpecRuleArgs(
                    column="address",
                    dimension="VALIDITY",
                    threshold=0.99,
                    non_null_expectation=gcp.dataplex.DatascanDataQualitySpecRuleNonNullExpectationArgs(),
                ),
                gcp.dataplex.DatascanDataQualitySpecRuleArgs(
                    column="council_district",
                    dimension="VALIDITY",
                    ignore_null=True,
                    threshold=0.9,
                    range_expectation=gcp.dataplex.DatascanDataQualitySpecRuleRangeExpectationArgs(
                        min_value="1",
                        max_value="10",
                        strict_min_enabled=True,
                        strict_max_enabled=False,
                    ),
                ),
                gcp.dataplex.DatascanDataQualitySpecRuleArgs(
                    column="power_type",
                    dimension="VALIDITY",
                    ignore_null=False,
                    regex_expectation=gcp.dataplex.DatascanDataQualitySpecRuleRegexExpectationArgs(
                        regex=".*solar.*",
                    ),
                ),
                gcp.dataplex.DatascanDataQualitySpecRuleArgs(
                    column="property_type",
                    dimension="VALIDITY",
                    ignore_null=False,
                    set_expectation=gcp.dataplex.DatascanDataQualitySpecRuleSetExpectationArgs(
                        values=[
                            "sidewalk",
                            "parkland",
                        ],
                    ),
                ),
                gcp.dataplex.DatascanDataQualitySpecRuleArgs(
                    column="address",
                    dimension="UNIQUENESS",
                    uniqueness_expectation=gcp.dataplex.DatascanDataQualitySpecRuleUniquenessExpectationArgs(),
                ),
                gcp.dataplex.DatascanDataQualitySpecRuleArgs(
                    column="number_of_docks",
                    dimension="VALIDITY",
                    statistic_range_expectation=gcp.dataplex.DatascanDataQualitySpecRuleStatisticRangeExpectationArgs(
                        statistic="MEAN",
                        min_value="5",
                        max_value="15",
                        strict_min_enabled=True,
                        strict_max_enabled=True,
                    ),
                ),
                gcp.dataplex.DatascanDataQualitySpecRuleArgs(
                    column="footprint_length",
                    dimension="VALIDITY",
                    row_condition_expectation=gcp.dataplex.DatascanDataQualitySpecRuleRowConditionExpectationArgs(
                        sql_expression="footprint_length > 0 AND footprint_length <= 10",
                    ),
                ),
                gcp.dataplex.DatascanDataQualitySpecRuleArgs(
                    dimension="VALIDITY",
                    table_condition_expectation=gcp.dataplex.DatascanDataQualitySpecRuleTableConditionExpectationArgs(
                        sql_expression="COUNT(*) > 0",
                    ),
                ),
            ],
        ),
        project="my-project-name")
    
    package main
    
    import (
    	"github.com/pulumi/pulumi-gcp/sdk/v7/go/gcp/dataplex"
    	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
    )
    
    func main() {
    	pulumi.Run(func(ctx *pulumi.Context) error {
    		_, err := dataplex.NewDatascan(ctx, "full_quality", &dataplex.DatascanArgs{
    			Location:    pulumi.String("us-central1"),
    			DisplayName: pulumi.String("Full Datascan Quality"),
    			DataScanId:  pulumi.String("dataquality-full"),
    			Description: pulumi.String("Example resource - Full Datascan Quality"),
    			Labels: pulumi.StringMap{
    				"author": pulumi.String("billing"),
    			},
    			Data: &dataplex.DatascanDataArgs{
    				Resource: pulumi.String("//bigquery.googleapis.com/projects/bigquery-public-data/datasets/austin_bikeshare/tables/bikeshare_stations"),
    			},
    			ExecutionSpec: &dataplex.DatascanExecutionSpecArgs{
    				Trigger: &dataplex.DatascanExecutionSpecTriggerArgs{
    					Schedule: &dataplex.DatascanExecutionSpecTriggerScheduleArgs{
    						Cron: pulumi.String("TZ=America/New_York 1 1 * * *"),
    					},
    				},
    				Field: pulumi.String("modified_date"),
    			},
    			DataQualitySpec: &dataplex.DatascanDataQualitySpecArgs{
    				SamplingPercent: pulumi.Float64(5),
    				RowFilter:       pulumi.String("station_id > 1000"),
    				Rules: dataplex.DatascanDataQualitySpecRuleArray{
    					&dataplex.DatascanDataQualitySpecRuleArgs{
    						Column:             pulumi.String("address"),
    						Dimension:          pulumi.String("VALIDITY"),
    						Threshold:          pulumi.Float64(0.99),
    						NonNullExpectation: nil,
    					},
    					&dataplex.DatascanDataQualitySpecRuleArgs{
    						Column:     pulumi.String("council_district"),
    						Dimension:  pulumi.String("VALIDITY"),
    						IgnoreNull: pulumi.Bool(true),
    						Threshold:  pulumi.Float64(0.9),
    						RangeExpectation: &dataplex.DatascanDataQualitySpecRuleRangeExpectationArgs{
    							MinValue:         pulumi.String("1"),
    							MaxValue:         pulumi.String("10"),
    							StrictMinEnabled: pulumi.Bool(true),
    							StrictMaxEnabled: pulumi.Bool(false),
    						},
    					},
    					&dataplex.DatascanDataQualitySpecRuleArgs{
    						Column:     pulumi.String("power_type"),
    						Dimension:  pulumi.String("VALIDITY"),
    						IgnoreNull: pulumi.Bool(false),
    						RegexExpectation: &dataplex.DatascanDataQualitySpecRuleRegexExpectationArgs{
    							Regex: pulumi.String(".*solar.*"),
    						},
    					},
    					&dataplex.DatascanDataQualitySpecRuleArgs{
    						Column:     pulumi.String("property_type"),
    						Dimension:  pulumi.String("VALIDITY"),
    						IgnoreNull: pulumi.Bool(false),
    						SetExpectation: &dataplex.DatascanDataQualitySpecRuleSetExpectationArgs{
    							Values: pulumi.StringArray{
    								pulumi.String("sidewalk"),
    								pulumi.String("parkland"),
    							},
    						},
    					},
    					&dataplex.DatascanDataQualitySpecRuleArgs{
    						Column:                pulumi.String("address"),
    						Dimension:             pulumi.String("UNIQUENESS"),
    						UniquenessExpectation: nil,
    					},
    					&dataplex.DatascanDataQualitySpecRuleArgs{
    						Column:    pulumi.String("number_of_docks"),
    						Dimension: pulumi.String("VALIDITY"),
    						StatisticRangeExpectation: &dataplex.DatascanDataQualitySpecRuleStatisticRangeExpectationArgs{
    							Statistic:        pulumi.String("MEAN"),
    							MinValue:         pulumi.String("5"),
    							MaxValue:         pulumi.String("15"),
    							StrictMinEnabled: pulumi.Bool(true),
    							StrictMaxEnabled: pulumi.Bool(true),
    						},
    					},
    					&dataplex.DatascanDataQualitySpecRuleArgs{
    						Column:    pulumi.String("footprint_length"),
    						Dimension: pulumi.String("VALIDITY"),
    						RowConditionExpectation: &dataplex.DatascanDataQualitySpecRuleRowConditionExpectationArgs{
    							SqlExpression: pulumi.String("footprint_length > 0 AND footprint_length <= 10"),
    						},
    					},
    					&dataplex.DatascanDataQualitySpecRuleArgs{
    						Dimension: pulumi.String("VALIDITY"),
    						TableConditionExpectation: &dataplex.DatascanDataQualitySpecRuleTableConditionExpectationArgs{
    							SqlExpression: pulumi.String("COUNT(*) > 0"),
    						},
    					},
    				},
    			},
    			Project: pulumi.String("my-project-name"),
    		})
    		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 fullQuality = new Gcp.DataPlex.Datascan("full_quality", new()
        {
            Location = "us-central1",
            DisplayName = "Full Datascan Quality",
            DataScanId = "dataquality-full",
            Description = "Example resource - Full Datascan Quality",
            Labels = 
            {
                { "author", "billing" },
            },
            Data = new Gcp.DataPlex.Inputs.DatascanDataArgs
            {
                Resource = "//bigquery.googleapis.com/projects/bigquery-public-data/datasets/austin_bikeshare/tables/bikeshare_stations",
            },
            ExecutionSpec = new Gcp.DataPlex.Inputs.DatascanExecutionSpecArgs
            {
                Trigger = new Gcp.DataPlex.Inputs.DatascanExecutionSpecTriggerArgs
                {
                    Schedule = new Gcp.DataPlex.Inputs.DatascanExecutionSpecTriggerScheduleArgs
                    {
                        Cron = "TZ=America/New_York 1 1 * * *",
                    },
                },
                Field = "modified_date",
            },
            DataQualitySpec = new Gcp.DataPlex.Inputs.DatascanDataQualitySpecArgs
            {
                SamplingPercent = 5,
                RowFilter = "station_id > 1000",
                Rules = new[]
                {
                    new Gcp.DataPlex.Inputs.DatascanDataQualitySpecRuleArgs
                    {
                        Column = "address",
                        Dimension = "VALIDITY",
                        Threshold = 0.99,
                        NonNullExpectation = null,
                    },
                    new Gcp.DataPlex.Inputs.DatascanDataQualitySpecRuleArgs
                    {
                        Column = "council_district",
                        Dimension = "VALIDITY",
                        IgnoreNull = true,
                        Threshold = 0.9,
                        RangeExpectation = new Gcp.DataPlex.Inputs.DatascanDataQualitySpecRuleRangeExpectationArgs
                        {
                            MinValue = "1",
                            MaxValue = "10",
                            StrictMinEnabled = true,
                            StrictMaxEnabled = false,
                        },
                    },
                    new Gcp.DataPlex.Inputs.DatascanDataQualitySpecRuleArgs
                    {
                        Column = "power_type",
                        Dimension = "VALIDITY",
                        IgnoreNull = false,
                        RegexExpectation = new Gcp.DataPlex.Inputs.DatascanDataQualitySpecRuleRegexExpectationArgs
                        {
                            Regex = ".*solar.*",
                        },
                    },
                    new Gcp.DataPlex.Inputs.DatascanDataQualitySpecRuleArgs
                    {
                        Column = "property_type",
                        Dimension = "VALIDITY",
                        IgnoreNull = false,
                        SetExpectation = new Gcp.DataPlex.Inputs.DatascanDataQualitySpecRuleSetExpectationArgs
                        {
                            Values = new[]
                            {
                                "sidewalk",
                                "parkland",
                            },
                        },
                    },
                    new Gcp.DataPlex.Inputs.DatascanDataQualitySpecRuleArgs
                    {
                        Column = "address",
                        Dimension = "UNIQUENESS",
                        UniquenessExpectation = null,
                    },
                    new Gcp.DataPlex.Inputs.DatascanDataQualitySpecRuleArgs
                    {
                        Column = "number_of_docks",
                        Dimension = "VALIDITY",
                        StatisticRangeExpectation = new Gcp.DataPlex.Inputs.DatascanDataQualitySpecRuleStatisticRangeExpectationArgs
                        {
                            Statistic = "MEAN",
                            MinValue = "5",
                            MaxValue = "15",
                            StrictMinEnabled = true,
                            StrictMaxEnabled = true,
                        },
                    },
                    new Gcp.DataPlex.Inputs.DatascanDataQualitySpecRuleArgs
                    {
                        Column = "footprint_length",
                        Dimension = "VALIDITY",
                        RowConditionExpectation = new Gcp.DataPlex.Inputs.DatascanDataQualitySpecRuleRowConditionExpectationArgs
                        {
                            SqlExpression = "footprint_length > 0 AND footprint_length <= 10",
                        },
                    },
                    new Gcp.DataPlex.Inputs.DatascanDataQualitySpecRuleArgs
                    {
                        Dimension = "VALIDITY",
                        TableConditionExpectation = new Gcp.DataPlex.Inputs.DatascanDataQualitySpecRuleTableConditionExpectationArgs
                        {
                            SqlExpression = "COUNT(*) > 0",
                        },
                    },
                },
            },
            Project = "my-project-name",
        });
    
    });
    
    package generated_program;
    
    import com.pulumi.Context;
    import com.pulumi.Pulumi;
    import com.pulumi.core.Output;
    import com.pulumi.gcp.dataplex.Datascan;
    import com.pulumi.gcp.dataplex.DatascanArgs;
    import com.pulumi.gcp.dataplex.inputs.DatascanDataArgs;
    import com.pulumi.gcp.dataplex.inputs.DatascanExecutionSpecArgs;
    import com.pulumi.gcp.dataplex.inputs.DatascanExecutionSpecTriggerArgs;
    import com.pulumi.gcp.dataplex.inputs.DatascanExecutionSpecTriggerScheduleArgs;
    import com.pulumi.gcp.dataplex.inputs.DatascanDataQualitySpecArgs;
    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 fullQuality = new Datascan("fullQuality", DatascanArgs.builder()
                .location("us-central1")
                .displayName("Full Datascan Quality")
                .dataScanId("dataquality-full")
                .description("Example resource - Full Datascan Quality")
                .labels(Map.of("author", "billing"))
                .data(DatascanDataArgs.builder()
                    .resource("//bigquery.googleapis.com/projects/bigquery-public-data/datasets/austin_bikeshare/tables/bikeshare_stations")
                    .build())
                .executionSpec(DatascanExecutionSpecArgs.builder()
                    .trigger(DatascanExecutionSpecTriggerArgs.builder()
                        .schedule(DatascanExecutionSpecTriggerScheduleArgs.builder()
                            .cron("TZ=America/New_York 1 1 * * *")
                            .build())
                        .build())
                    .field("modified_date")
                    .build())
                .dataQualitySpec(DatascanDataQualitySpecArgs.builder()
                    .samplingPercent(5)
                    .rowFilter("station_id > 1000")
                    .rules(                
                        DatascanDataQualitySpecRuleArgs.builder()
                            .column("address")
                            .dimension("VALIDITY")
                            .threshold(0.99)
                            .nonNullExpectation()
                            .build(),
                        DatascanDataQualitySpecRuleArgs.builder()
                            .column("council_district")
                            .dimension("VALIDITY")
                            .ignoreNull(true)
                            .threshold(0.9)
                            .rangeExpectation(DatascanDataQualitySpecRuleRangeExpectationArgs.builder()
                                .minValue(1)
                                .maxValue(10)
                                .strictMinEnabled(true)
                                .strictMaxEnabled(false)
                                .build())
                            .build(),
                        DatascanDataQualitySpecRuleArgs.builder()
                            .column("power_type")
                            .dimension("VALIDITY")
                            .ignoreNull(false)
                            .regexExpectation(DatascanDataQualitySpecRuleRegexExpectationArgs.builder()
                                .regex(".*solar.*")
                                .build())
                            .build(),
                        DatascanDataQualitySpecRuleArgs.builder()
                            .column("property_type")
                            .dimension("VALIDITY")
                            .ignoreNull(false)
                            .setExpectation(DatascanDataQualitySpecRuleSetExpectationArgs.builder()
                                .values(                            
                                    "sidewalk",
                                    "parkland")
                                .build())
                            .build(),
                        DatascanDataQualitySpecRuleArgs.builder()
                            .column("address")
                            .dimension("UNIQUENESS")
                            .uniquenessExpectation()
                            .build(),
                        DatascanDataQualitySpecRuleArgs.builder()
                            .column("number_of_docks")
                            .dimension("VALIDITY")
                            .statisticRangeExpectation(DatascanDataQualitySpecRuleStatisticRangeExpectationArgs.builder()
                                .statistic("MEAN")
                                .minValue(5)
                                .maxValue(15)
                                .strictMinEnabled(true)
                                .strictMaxEnabled(true)
                                .build())
                            .build(),
                        DatascanDataQualitySpecRuleArgs.builder()
                            .column("footprint_length")
                            .dimension("VALIDITY")
                            .rowConditionExpectation(DatascanDataQualitySpecRuleRowConditionExpectationArgs.builder()
                                .sqlExpression("footprint_length > 0 AND footprint_length <= 10")
                                .build())
                            .build(),
                        DatascanDataQualitySpecRuleArgs.builder()
                            .dimension("VALIDITY")
                            .tableConditionExpectation(DatascanDataQualitySpecRuleTableConditionExpectationArgs.builder()
                                .sqlExpression("COUNT(*) > 0")
                                .build())
                            .build())
                    .build())
                .project("my-project-name")
                .build());
    
        }
    }
    
    resources:
      fullQuality:
        type: gcp:dataplex:Datascan
        name: full_quality
        properties:
          location: us-central1
          displayName: Full Datascan Quality
          dataScanId: dataquality-full
          description: Example resource - Full Datascan Quality
          labels:
            author: billing
          data:
            resource: //bigquery.googleapis.com/projects/bigquery-public-data/datasets/austin_bikeshare/tables/bikeshare_stations
          executionSpec:
            trigger:
              schedule:
                cron: TZ=America/New_York 1 1 * * *
            field: modified_date
          dataQualitySpec:
            samplingPercent: 5
            rowFilter: station_id > 1000
            rules:
              - column: address
                dimension: VALIDITY
                threshold: 0.99
                nonNullExpectation: {}
              - column: council_district
                dimension: VALIDITY
                ignoreNull: true
                threshold: 0.9
                rangeExpectation:
                  minValue: 1
                  maxValue: 10
                  strictMinEnabled: true
                  strictMaxEnabled: false
              - column: power_type
                dimension: VALIDITY
                ignoreNull: false
                regexExpectation:
                  regex: .*solar.*
              - column: property_type
                dimension: VALIDITY
                ignoreNull: false
                setExpectation:
                  values:
                    - sidewalk
                    - parkland
              - column: address
                dimension: UNIQUENESS
                uniquenessExpectation: {}
              - column: number_of_docks
                dimension: VALIDITY
                statisticRangeExpectation:
                  statistic: MEAN
                  minValue: 5
                  maxValue: 15
                  strictMinEnabled: true
                  strictMaxEnabled: true
              - column: footprint_length
                dimension: VALIDITY
                rowConditionExpectation:
                  sqlExpression: footprint_length > 0 AND footprint_length <= 10
              - dimension: VALIDITY
                tableConditionExpectation:
                  sqlExpression: COUNT(*) > 0
          project: my-project-name
    

    Create Datascan Resource

    Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.

    Constructor syntax

    new Datascan(name: string, args: DatascanArgs, opts?: CustomResourceOptions);
    @overload
    def Datascan(resource_name: str,
                 args: DatascanArgs,
                 opts: Optional[ResourceOptions] = None)
    
    @overload
    def Datascan(resource_name: str,
                 opts: Optional[ResourceOptions] = None,
                 data: Optional[DatascanDataArgs] = None,
                 data_scan_id: Optional[str] = None,
                 execution_spec: Optional[DatascanExecutionSpecArgs] = None,
                 location: Optional[str] = None,
                 data_profile_spec: Optional[DatascanDataProfileSpecArgs] = None,
                 data_quality_spec: Optional[DatascanDataQualitySpecArgs] = None,
                 description: Optional[str] = None,
                 display_name: Optional[str] = None,
                 labels: Optional[Mapping[str, str]] = None,
                 project: Optional[str] = None)
    func NewDatascan(ctx *Context, name string, args DatascanArgs, opts ...ResourceOption) (*Datascan, error)
    public Datascan(string name, DatascanArgs args, CustomResourceOptions? opts = null)
    public Datascan(String name, DatascanArgs args)
    public Datascan(String name, DatascanArgs args, CustomResourceOptions options)
    
    type: gcp:dataplex:Datascan
    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 DatascanArgs
    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 DatascanArgs
    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 DatascanArgs
    The arguments to resource properties.
    opts ResourceOption
    Bag of options to control resource's behavior.
    name string
    The unique name of the resource.
    args DatascanArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    name String
    The unique name of the resource.
    args DatascanArgs
    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 datascanResource = new Gcp.DataPlex.Datascan("datascanResource", new()
    {
        Data = new Gcp.DataPlex.Inputs.DatascanDataArgs
        {
            Entity = "string",
            Resource = "string",
        },
        DataScanId = "string",
        ExecutionSpec = new Gcp.DataPlex.Inputs.DatascanExecutionSpecArgs
        {
            Trigger = new Gcp.DataPlex.Inputs.DatascanExecutionSpecTriggerArgs
            {
                OnDemand = null,
                Schedule = new Gcp.DataPlex.Inputs.DatascanExecutionSpecTriggerScheduleArgs
                {
                    Cron = "string",
                },
            },
            Field = "string",
        },
        Location = "string",
        DataProfileSpec = new Gcp.DataPlex.Inputs.DatascanDataProfileSpecArgs
        {
            ExcludeFields = new Gcp.DataPlex.Inputs.DatascanDataProfileSpecExcludeFieldsArgs
            {
                FieldNames = new[]
                {
                    "string",
                },
            },
            IncludeFields = new Gcp.DataPlex.Inputs.DatascanDataProfileSpecIncludeFieldsArgs
            {
                FieldNames = new[]
                {
                    "string",
                },
            },
            PostScanActions = new Gcp.DataPlex.Inputs.DatascanDataProfileSpecPostScanActionsArgs
            {
                BigqueryExport = new Gcp.DataPlex.Inputs.DatascanDataProfileSpecPostScanActionsBigqueryExportArgs
                {
                    ResultsTable = "string",
                },
            },
            RowFilter = "string",
            SamplingPercent = 0,
        },
        DataQualitySpec = new Gcp.DataPlex.Inputs.DatascanDataQualitySpecArgs
        {
            PostScanActions = new Gcp.DataPlex.Inputs.DatascanDataQualitySpecPostScanActionsArgs
            {
                BigqueryExport = new Gcp.DataPlex.Inputs.DatascanDataQualitySpecPostScanActionsBigqueryExportArgs
                {
                    ResultsTable = "string",
                },
            },
            RowFilter = "string",
            Rules = new[]
            {
                new Gcp.DataPlex.Inputs.DatascanDataQualitySpecRuleArgs
                {
                    Dimension = "string",
                    RangeExpectation = new Gcp.DataPlex.Inputs.DatascanDataQualitySpecRuleRangeExpectationArgs
                    {
                        MaxValue = "string",
                        MinValue = "string",
                        StrictMaxEnabled = false,
                        StrictMinEnabled = false,
                    },
                    Description = "string",
                    IgnoreNull = false,
                    Name = "string",
                    NonNullExpectation = null,
                    Column = "string",
                    RegexExpectation = new Gcp.DataPlex.Inputs.DatascanDataQualitySpecRuleRegexExpectationArgs
                    {
                        Regex = "string",
                    },
                    RowConditionExpectation = new Gcp.DataPlex.Inputs.DatascanDataQualitySpecRuleRowConditionExpectationArgs
                    {
                        SqlExpression = "string",
                    },
                    SetExpectation = new Gcp.DataPlex.Inputs.DatascanDataQualitySpecRuleSetExpectationArgs
                    {
                        Values = new[]
                        {
                            "string",
                        },
                    },
                    StatisticRangeExpectation = new Gcp.DataPlex.Inputs.DatascanDataQualitySpecRuleStatisticRangeExpectationArgs
                    {
                        Statistic = "string",
                        MaxValue = "string",
                        MinValue = "string",
                        StrictMaxEnabled = false,
                        StrictMinEnabled = false,
                    },
                    TableConditionExpectation = new Gcp.DataPlex.Inputs.DatascanDataQualitySpecRuleTableConditionExpectationArgs
                    {
                        SqlExpression = "string",
                    },
                    Threshold = 0,
                    UniquenessExpectation = null,
                },
            },
            SamplingPercent = 0,
        },
        Description = "string",
        DisplayName = "string",
        Labels = 
        {
            { "string", "string" },
        },
        Project = "string",
    });
    
    example, err := dataplex.NewDatascan(ctx, "datascanResource", &dataplex.DatascanArgs{
    	Data: &dataplex.DatascanDataArgs{
    		Entity:   pulumi.String("string"),
    		Resource: pulumi.String("string"),
    	},
    	DataScanId: pulumi.String("string"),
    	ExecutionSpec: &dataplex.DatascanExecutionSpecArgs{
    		Trigger: &dataplex.DatascanExecutionSpecTriggerArgs{
    			OnDemand: nil,
    			Schedule: &dataplex.DatascanExecutionSpecTriggerScheduleArgs{
    				Cron: pulumi.String("string"),
    			},
    		},
    		Field: pulumi.String("string"),
    	},
    	Location: pulumi.String("string"),
    	DataProfileSpec: &dataplex.DatascanDataProfileSpecArgs{
    		ExcludeFields: &dataplex.DatascanDataProfileSpecExcludeFieldsArgs{
    			FieldNames: pulumi.StringArray{
    				pulumi.String("string"),
    			},
    		},
    		IncludeFields: &dataplex.DatascanDataProfileSpecIncludeFieldsArgs{
    			FieldNames: pulumi.StringArray{
    				pulumi.String("string"),
    			},
    		},
    		PostScanActions: &dataplex.DatascanDataProfileSpecPostScanActionsArgs{
    			BigqueryExport: &dataplex.DatascanDataProfileSpecPostScanActionsBigqueryExportArgs{
    				ResultsTable: pulumi.String("string"),
    			},
    		},
    		RowFilter:       pulumi.String("string"),
    		SamplingPercent: pulumi.Float64(0),
    	},
    	DataQualitySpec: &dataplex.DatascanDataQualitySpecArgs{
    		PostScanActions: &dataplex.DatascanDataQualitySpecPostScanActionsArgs{
    			BigqueryExport: &dataplex.DatascanDataQualitySpecPostScanActionsBigqueryExportArgs{
    				ResultsTable: pulumi.String("string"),
    			},
    		},
    		RowFilter: pulumi.String("string"),
    		Rules: dataplex.DatascanDataQualitySpecRuleArray{
    			&dataplex.DatascanDataQualitySpecRuleArgs{
    				Dimension: pulumi.String("string"),
    				RangeExpectation: &dataplex.DatascanDataQualitySpecRuleRangeExpectationArgs{
    					MaxValue:         pulumi.String("string"),
    					MinValue:         pulumi.String("string"),
    					StrictMaxEnabled: pulumi.Bool(false),
    					StrictMinEnabled: pulumi.Bool(false),
    				},
    				Description:        pulumi.String("string"),
    				IgnoreNull:         pulumi.Bool(false),
    				Name:               pulumi.String("string"),
    				NonNullExpectation: nil,
    				Column:             pulumi.String("string"),
    				RegexExpectation: &dataplex.DatascanDataQualitySpecRuleRegexExpectationArgs{
    					Regex: pulumi.String("string"),
    				},
    				RowConditionExpectation: &dataplex.DatascanDataQualitySpecRuleRowConditionExpectationArgs{
    					SqlExpression: pulumi.String("string"),
    				},
    				SetExpectation: &dataplex.DatascanDataQualitySpecRuleSetExpectationArgs{
    					Values: pulumi.StringArray{
    						pulumi.String("string"),
    					},
    				},
    				StatisticRangeExpectation: &dataplex.DatascanDataQualitySpecRuleStatisticRangeExpectationArgs{
    					Statistic:        pulumi.String("string"),
    					MaxValue:         pulumi.String("string"),
    					MinValue:         pulumi.String("string"),
    					StrictMaxEnabled: pulumi.Bool(false),
    					StrictMinEnabled: pulumi.Bool(false),
    				},
    				TableConditionExpectation: &dataplex.DatascanDataQualitySpecRuleTableConditionExpectationArgs{
    					SqlExpression: pulumi.String("string"),
    				},
    				Threshold:             pulumi.Float64(0),
    				UniquenessExpectation: nil,
    			},
    		},
    		SamplingPercent: pulumi.Float64(0),
    	},
    	Description: pulumi.String("string"),
    	DisplayName: pulumi.String("string"),
    	Labels: pulumi.StringMap{
    		"string": pulumi.String("string"),
    	},
    	Project: pulumi.String("string"),
    })
    
    var datascanResource = new Datascan("datascanResource", DatascanArgs.builder()
        .data(DatascanDataArgs.builder()
            .entity("string")
            .resource("string")
            .build())
        .dataScanId("string")
        .executionSpec(DatascanExecutionSpecArgs.builder()
            .trigger(DatascanExecutionSpecTriggerArgs.builder()
                .onDemand()
                .schedule(DatascanExecutionSpecTriggerScheduleArgs.builder()
                    .cron("string")
                    .build())
                .build())
            .field("string")
            .build())
        .location("string")
        .dataProfileSpec(DatascanDataProfileSpecArgs.builder()
            .excludeFields(DatascanDataProfileSpecExcludeFieldsArgs.builder()
                .fieldNames("string")
                .build())
            .includeFields(DatascanDataProfileSpecIncludeFieldsArgs.builder()
                .fieldNames("string")
                .build())
            .postScanActions(DatascanDataProfileSpecPostScanActionsArgs.builder()
                .bigqueryExport(DatascanDataProfileSpecPostScanActionsBigqueryExportArgs.builder()
                    .resultsTable("string")
                    .build())
                .build())
            .rowFilter("string")
            .samplingPercent(0)
            .build())
        .dataQualitySpec(DatascanDataQualitySpecArgs.builder()
            .postScanActions(DatascanDataQualitySpecPostScanActionsArgs.builder()
                .bigqueryExport(DatascanDataQualitySpecPostScanActionsBigqueryExportArgs.builder()
                    .resultsTable("string")
                    .build())
                .build())
            .rowFilter("string")
            .rules(DatascanDataQualitySpecRuleArgs.builder()
                .dimension("string")
                .rangeExpectation(DatascanDataQualitySpecRuleRangeExpectationArgs.builder()
                    .maxValue("string")
                    .minValue("string")
                    .strictMaxEnabled(false)
                    .strictMinEnabled(false)
                    .build())
                .description("string")
                .ignoreNull(false)
                .name("string")
                .nonNullExpectation()
                .column("string")
                .regexExpectation(DatascanDataQualitySpecRuleRegexExpectationArgs.builder()
                    .regex("string")
                    .build())
                .rowConditionExpectation(DatascanDataQualitySpecRuleRowConditionExpectationArgs.builder()
                    .sqlExpression("string")
                    .build())
                .setExpectation(DatascanDataQualitySpecRuleSetExpectationArgs.builder()
                    .values("string")
                    .build())
                .statisticRangeExpectation(DatascanDataQualitySpecRuleStatisticRangeExpectationArgs.builder()
                    .statistic("string")
                    .maxValue("string")
                    .minValue("string")
                    .strictMaxEnabled(false)
                    .strictMinEnabled(false)
                    .build())
                .tableConditionExpectation(DatascanDataQualitySpecRuleTableConditionExpectationArgs.builder()
                    .sqlExpression("string")
                    .build())
                .threshold(0)
                .uniquenessExpectation()
                .build())
            .samplingPercent(0)
            .build())
        .description("string")
        .displayName("string")
        .labels(Map.of("string", "string"))
        .project("string")
        .build());
    
    datascan_resource = gcp.dataplex.Datascan("datascanResource",
        data=gcp.dataplex.DatascanDataArgs(
            entity="string",
            resource="string",
        ),
        data_scan_id="string",
        execution_spec=gcp.dataplex.DatascanExecutionSpecArgs(
            trigger=gcp.dataplex.DatascanExecutionSpecTriggerArgs(
                on_demand=gcp.dataplex.DatascanExecutionSpecTriggerOnDemandArgs(),
                schedule=gcp.dataplex.DatascanExecutionSpecTriggerScheduleArgs(
                    cron="string",
                ),
            ),
            field="string",
        ),
        location="string",
        data_profile_spec=gcp.dataplex.DatascanDataProfileSpecArgs(
            exclude_fields=gcp.dataplex.DatascanDataProfileSpecExcludeFieldsArgs(
                field_names=["string"],
            ),
            include_fields=gcp.dataplex.DatascanDataProfileSpecIncludeFieldsArgs(
                field_names=["string"],
            ),
            post_scan_actions=gcp.dataplex.DatascanDataProfileSpecPostScanActionsArgs(
                bigquery_export=gcp.dataplex.DatascanDataProfileSpecPostScanActionsBigqueryExportArgs(
                    results_table="string",
                ),
            ),
            row_filter="string",
            sampling_percent=0,
        ),
        data_quality_spec=gcp.dataplex.DatascanDataQualitySpecArgs(
            post_scan_actions=gcp.dataplex.DatascanDataQualitySpecPostScanActionsArgs(
                bigquery_export=gcp.dataplex.DatascanDataQualitySpecPostScanActionsBigqueryExportArgs(
                    results_table="string",
                ),
            ),
            row_filter="string",
            rules=[gcp.dataplex.DatascanDataQualitySpecRuleArgs(
                dimension="string",
                range_expectation=gcp.dataplex.DatascanDataQualitySpecRuleRangeExpectationArgs(
                    max_value="string",
                    min_value="string",
                    strict_max_enabled=False,
                    strict_min_enabled=False,
                ),
                description="string",
                ignore_null=False,
                name="string",
                non_null_expectation=gcp.dataplex.DatascanDataQualitySpecRuleNonNullExpectationArgs(),
                column="string",
                regex_expectation=gcp.dataplex.DatascanDataQualitySpecRuleRegexExpectationArgs(
                    regex="string",
                ),
                row_condition_expectation=gcp.dataplex.DatascanDataQualitySpecRuleRowConditionExpectationArgs(
                    sql_expression="string",
                ),
                set_expectation=gcp.dataplex.DatascanDataQualitySpecRuleSetExpectationArgs(
                    values=["string"],
                ),
                statistic_range_expectation=gcp.dataplex.DatascanDataQualitySpecRuleStatisticRangeExpectationArgs(
                    statistic="string",
                    max_value="string",
                    min_value="string",
                    strict_max_enabled=False,
                    strict_min_enabled=False,
                ),
                table_condition_expectation=gcp.dataplex.DatascanDataQualitySpecRuleTableConditionExpectationArgs(
                    sql_expression="string",
                ),
                threshold=0,
                uniqueness_expectation=gcp.dataplex.DatascanDataQualitySpecRuleUniquenessExpectationArgs(),
            )],
            sampling_percent=0,
        ),
        description="string",
        display_name="string",
        labels={
            "string": "string",
        },
        project="string")
    
    const datascanResource = new gcp.dataplex.Datascan("datascanResource", {
        data: {
            entity: "string",
            resource: "string",
        },
        dataScanId: "string",
        executionSpec: {
            trigger: {
                onDemand: {},
                schedule: {
                    cron: "string",
                },
            },
            field: "string",
        },
        location: "string",
        dataProfileSpec: {
            excludeFields: {
                fieldNames: ["string"],
            },
            includeFields: {
                fieldNames: ["string"],
            },
            postScanActions: {
                bigqueryExport: {
                    resultsTable: "string",
                },
            },
            rowFilter: "string",
            samplingPercent: 0,
        },
        dataQualitySpec: {
            postScanActions: {
                bigqueryExport: {
                    resultsTable: "string",
                },
            },
            rowFilter: "string",
            rules: [{
                dimension: "string",
                rangeExpectation: {
                    maxValue: "string",
                    minValue: "string",
                    strictMaxEnabled: false,
                    strictMinEnabled: false,
                },
                description: "string",
                ignoreNull: false,
                name: "string",
                nonNullExpectation: {},
                column: "string",
                regexExpectation: {
                    regex: "string",
                },
                rowConditionExpectation: {
                    sqlExpression: "string",
                },
                setExpectation: {
                    values: ["string"],
                },
                statisticRangeExpectation: {
                    statistic: "string",
                    maxValue: "string",
                    minValue: "string",
                    strictMaxEnabled: false,
                    strictMinEnabled: false,
                },
                tableConditionExpectation: {
                    sqlExpression: "string",
                },
                threshold: 0,
                uniquenessExpectation: {},
            }],
            samplingPercent: 0,
        },
        description: "string",
        displayName: "string",
        labels: {
            string: "string",
        },
        project: "string",
    });
    
    type: gcp:dataplex:Datascan
    properties:
        data:
            entity: string
            resource: string
        dataProfileSpec:
            excludeFields:
                fieldNames:
                    - string
            includeFields:
                fieldNames:
                    - string
            postScanActions:
                bigqueryExport:
                    resultsTable: string
            rowFilter: string
            samplingPercent: 0
        dataQualitySpec:
            postScanActions:
                bigqueryExport:
                    resultsTable: string
            rowFilter: string
            rules:
                - column: string
                  description: string
                  dimension: string
                  ignoreNull: false
                  name: string
                  nonNullExpectation: {}
                  rangeExpectation:
                    maxValue: string
                    minValue: string
                    strictMaxEnabled: false
                    strictMinEnabled: false
                  regexExpectation:
                    regex: string
                  rowConditionExpectation:
                    sqlExpression: string
                  setExpectation:
                    values:
                        - string
                  statisticRangeExpectation:
                    maxValue: string
                    minValue: string
                    statistic: string
                    strictMaxEnabled: false
                    strictMinEnabled: false
                  tableConditionExpectation:
                    sqlExpression: string
                  threshold: 0
                  uniquenessExpectation: {}
            samplingPercent: 0
        dataScanId: string
        description: string
        displayName: string
        executionSpec:
            field: string
            trigger:
                onDemand: {}
                schedule:
                    cron: string
        labels:
            string: string
        location: string
        project: string
    

    Datascan 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 Datascan resource accepts the following input properties:

    Data DatascanData
    The data source for DataScan. Structure is documented below.
    DataScanId string
    DataScan identifier. Must contain only lowercase letters, numbers and hyphens. Must start with a letter. Must end with a number or a letter.
    ExecutionSpec DatascanExecutionSpec
    DataScan execution settings. Structure is documented below.
    Location string
    The location where the data scan should reside.
    DataProfileSpec DatascanDataProfileSpec
    DataProfileScan related setting.
    DataQualitySpec DatascanDataQualitySpec
    DataQualityScan related setting.
    Description string
    Description of the scan.
    DisplayName string
    User friendly display name.
    Labels Dictionary<string, string>
    User-defined labels for the scan. A list of key->value pairs. 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.
    Project string
    Data DatascanDataArgs
    The data source for DataScan. Structure is documented below.
    DataScanId string
    DataScan identifier. Must contain only lowercase letters, numbers and hyphens. Must start with a letter. Must end with a number or a letter.
    ExecutionSpec DatascanExecutionSpecArgs
    DataScan execution settings. Structure is documented below.
    Location string
    The location where the data scan should reside.
    DataProfileSpec DatascanDataProfileSpecArgs
    DataProfileScan related setting.
    DataQualitySpec DatascanDataQualitySpecArgs
    DataQualityScan related setting.
    Description string
    Description of the scan.
    DisplayName string
    User friendly display name.
    Labels map[string]string
    User-defined labels for the scan. A list of key->value pairs. 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.
    Project string
    data DatascanData
    The data source for DataScan. Structure is documented below.
    dataScanId String
    DataScan identifier. Must contain only lowercase letters, numbers and hyphens. Must start with a letter. Must end with a number or a letter.
    executionSpec DatascanExecutionSpec
    DataScan execution settings. Structure is documented below.
    location String
    The location where the data scan should reside.
    dataProfileSpec DatascanDataProfileSpec
    DataProfileScan related setting.
    dataQualitySpec DatascanDataQualitySpec
    DataQualityScan related setting.
    description String
    Description of the scan.
    displayName String
    User friendly display name.
    labels Map<String,String>
    User-defined labels for the scan. A list of key->value pairs. 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.
    project String
    data DatascanData
    The data source for DataScan. Structure is documented below.
    dataScanId string
    DataScan identifier. Must contain only lowercase letters, numbers and hyphens. Must start with a letter. Must end with a number or a letter.
    executionSpec DatascanExecutionSpec
    DataScan execution settings. Structure is documented below.
    location string
    The location where the data scan should reside.
    dataProfileSpec DatascanDataProfileSpec
    DataProfileScan related setting.
    dataQualitySpec DatascanDataQualitySpec
    DataQualityScan related setting.
    description string
    Description of the scan.
    displayName string
    User friendly display name.
    labels {[key: string]: string}
    User-defined labels for the scan. A list of key->value pairs. 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.
    project string
    data DatascanDataArgs
    The data source for DataScan. Structure is documented below.
    data_scan_id str
    DataScan identifier. Must contain only lowercase letters, numbers and hyphens. Must start with a letter. Must end with a number or a letter.
    execution_spec DatascanExecutionSpecArgs
    DataScan execution settings. Structure is documented below.
    location str
    The location where the data scan should reside.
    data_profile_spec DatascanDataProfileSpecArgs
    DataProfileScan related setting.
    data_quality_spec DatascanDataQualitySpecArgs
    DataQualityScan related setting.
    description str
    Description of the scan.
    display_name str
    User friendly display name.
    labels Mapping[str, str]
    User-defined labels for the scan. A list of key->value pairs. 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.
    project str
    data Property Map
    The data source for DataScan. Structure is documented below.
    dataScanId String
    DataScan identifier. Must contain only lowercase letters, numbers and hyphens. Must start with a letter. Must end with a number or a letter.
    executionSpec Property Map
    DataScan execution settings. Structure is documented below.
    location String
    The location where the data scan should reside.
    dataProfileSpec Property Map
    DataProfileScan related setting.
    dataQualitySpec Property Map
    DataQualityScan related setting.
    description String
    Description of the scan.
    displayName String
    User friendly display name.
    labels Map<String>
    User-defined labels for the scan. A list of key->value pairs. 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.
    project String

    Outputs

    All input properties are implicitly available as output properties. Additionally, the Datascan resource produces the following output properties:

    CreateTime string
    The time when the scan was created.
    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.
    ExecutionStatuses List<DatascanExecutionStatus>
    Status of the data scan execution. Structure is documented below.
    Id string
    The provider-assigned unique ID for this managed resource.
    Name string
    The relative resource name of the scan, of the form: projects/{project}/locations/{locationId}/dataScans/{datascan_id}, where project refers to a project_id or project_number and locationId refers to a GCP region.
    PulumiLabels Dictionary<string, string>
    The combination of labels configured directly on the resource and default labels configured on the provider.
    State string
    Current state of the DataScan.
    Type string
    The type of DataScan.
    Uid string
    System generated globally unique ID for the scan. This ID will be different if the scan is deleted and re-created with the same name.
    UpdateTime string
    The time when the scan was last updated.
    CreateTime string
    The time when the scan was created.
    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.
    ExecutionStatuses []DatascanExecutionStatus
    Status of the data scan execution. Structure is documented below.
    Id string
    The provider-assigned unique ID for this managed resource.
    Name string
    The relative resource name of the scan, of the form: projects/{project}/locations/{locationId}/dataScans/{datascan_id}, where project refers to a project_id or project_number and locationId refers to a GCP region.
    PulumiLabels map[string]string
    The combination of labels configured directly on the resource and default labels configured on the provider.
    State string
    Current state of the DataScan.
    Type string
    The type of DataScan.
    Uid string
    System generated globally unique ID for the scan. This ID will be different if the scan is deleted and re-created with the same name.
    UpdateTime string
    The time when the scan was last updated.
    createTime String
    The time when the scan was created.
    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.
    executionStatuses List<DatascanExecutionStatus>
    Status of the data scan execution. Structure is documented below.
    id String
    The provider-assigned unique ID for this managed resource.
    name String
    The relative resource name of the scan, of the form: projects/{project}/locations/{locationId}/dataScans/{datascan_id}, where project refers to a project_id or project_number and locationId refers to a GCP region.
    pulumiLabels Map<String,String>
    The combination of labels configured directly on the resource and default labels configured on the provider.
    state String
    Current state of the DataScan.
    type String
    The type of DataScan.
    uid String
    System generated globally unique ID for the scan. This ID will be different if the scan is deleted and re-created with the same name.
    updateTime String
    The time when the scan was last updated.
    createTime string
    The time when the scan was created.
    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.
    executionStatuses DatascanExecutionStatus[]
    Status of the data scan execution. Structure is documented below.
    id string
    The provider-assigned unique ID for this managed resource.
    name string
    The relative resource name of the scan, of the form: projects/{project}/locations/{locationId}/dataScans/{datascan_id}, where project refers to a project_id or project_number and locationId refers to a GCP region.
    pulumiLabels {[key: string]: string}
    The combination of labels configured directly on the resource and default labels configured on the provider.
    state string
    Current state of the DataScan.
    type string
    The type of DataScan.
    uid string
    System generated globally unique ID for the scan. This ID will be different if the scan is deleted and re-created with the same name.
    updateTime string
    The time when the scan was last updated.
    create_time str
    The time when the scan was created.
    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.
    execution_statuses Sequence[DatascanExecutionStatus]
    Status of the data scan execution. Structure is documented below.
    id str
    The provider-assigned unique ID for this managed resource.
    name str
    The relative resource name of the scan, of the form: projects/{project}/locations/{locationId}/dataScans/{datascan_id}, where project refers to a project_id or project_number and locationId refers to a GCP region.
    pulumi_labels Mapping[str, str]
    The combination of labels configured directly on the resource and default labels configured on the provider.
    state str
    Current state of the DataScan.
    type str
    The type of DataScan.
    uid str
    System generated globally unique ID for the scan. This ID will be different if the scan is deleted and re-created with the same name.
    update_time str
    The time when the scan was last updated.
    createTime String
    The time when the scan was created.
    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.
    executionStatuses List<Property Map>
    Status of the data scan execution. Structure is documented below.
    id String
    The provider-assigned unique ID for this managed resource.
    name String
    The relative resource name of the scan, of the form: projects/{project}/locations/{locationId}/dataScans/{datascan_id}, where project refers to a project_id or project_number and locationId refers to a GCP region.
    pulumiLabels Map<String>
    The combination of labels configured directly on the resource and default labels configured on the provider.
    state String
    Current state of the DataScan.
    type String
    The type of DataScan.
    uid String
    System generated globally unique ID for the scan. This ID will be different if the scan is deleted and re-created with the same name.
    updateTime String
    The time when the scan was last updated.

    Look up Existing Datascan Resource

    Get an existing Datascan 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?: DatascanState, opts?: CustomResourceOptions): Datascan
    @staticmethod
    def get(resource_name: str,
            id: str,
            opts: Optional[ResourceOptions] = None,
            create_time: Optional[str] = None,
            data: Optional[DatascanDataArgs] = None,
            data_profile_spec: Optional[DatascanDataProfileSpecArgs] = None,
            data_quality_spec: Optional[DatascanDataQualitySpecArgs] = None,
            data_scan_id: Optional[str] = None,
            description: Optional[str] = None,
            display_name: Optional[str] = None,
            effective_labels: Optional[Mapping[str, str]] = None,
            execution_spec: Optional[DatascanExecutionSpecArgs] = None,
            execution_statuses: Optional[Sequence[DatascanExecutionStatusArgs]] = None,
            labels: Optional[Mapping[str, str]] = None,
            location: Optional[str] = None,
            name: Optional[str] = None,
            project: Optional[str] = None,
            pulumi_labels: Optional[Mapping[str, str]] = None,
            state: Optional[str] = None,
            type: Optional[str] = None,
            uid: Optional[str] = None,
            update_time: Optional[str] = None) -> Datascan
    func GetDatascan(ctx *Context, name string, id IDInput, state *DatascanState, opts ...ResourceOption) (*Datascan, error)
    public static Datascan Get(string name, Input<string> id, DatascanState? state, CustomResourceOptions? opts = null)
    public static Datascan get(String name, Output<String> id, DatascanState 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:
    CreateTime string
    The time when the scan was created.
    Data DatascanData
    The data source for DataScan. Structure is documented below.
    DataProfileSpec DatascanDataProfileSpec
    DataProfileScan related setting.
    DataQualitySpec DatascanDataQualitySpec
    DataQualityScan related setting.
    DataScanId string
    DataScan identifier. Must contain only lowercase letters, numbers and hyphens. Must start with a letter. Must end with a number or a letter.
    Description string
    Description of the scan.
    DisplayName string
    User friendly display name.
    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.
    ExecutionSpec DatascanExecutionSpec
    DataScan execution settings. Structure is documented below.
    ExecutionStatuses List<DatascanExecutionStatus>
    Status of the data scan execution. Structure is documented below.
    Labels Dictionary<string, string>
    User-defined labels for the scan. A list of key->value pairs. 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.
    Location string
    The location where the data scan should reside.
    Name string
    The relative resource name of the scan, of the form: projects/{project}/locations/{locationId}/dataScans/{datascan_id}, where project refers to a project_id or project_number and locationId refers to a GCP region.
    Project string
    PulumiLabels Dictionary<string, string>
    The combination of labels configured directly on the resource and default labels configured on the provider.
    State string
    Current state of the DataScan.
    Type string
    The type of DataScan.
    Uid string
    System generated globally unique ID for the scan. This ID will be different if the scan is deleted and re-created with the same name.
    UpdateTime string
    The time when the scan was last updated.
    CreateTime string
    The time when the scan was created.
    Data DatascanDataArgs
    The data source for DataScan. Structure is documented below.
    DataProfileSpec DatascanDataProfileSpecArgs
    DataProfileScan related setting.
    DataQualitySpec DatascanDataQualitySpecArgs
    DataQualityScan related setting.
    DataScanId string
    DataScan identifier. Must contain only lowercase letters, numbers and hyphens. Must start with a letter. Must end with a number or a letter.
    Description string
    Description of the scan.
    DisplayName string
    User friendly display name.
    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.
    ExecutionSpec DatascanExecutionSpecArgs
    DataScan execution settings. Structure is documented below.
    ExecutionStatuses []DatascanExecutionStatusArgs
    Status of the data scan execution. Structure is documented below.
    Labels map[string]string
    User-defined labels for the scan. A list of key->value pairs. 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.
    Location string
    The location where the data scan should reside.
    Name string
    The relative resource name of the scan, of the form: projects/{project}/locations/{locationId}/dataScans/{datascan_id}, where project refers to a project_id or project_number and locationId refers to a GCP region.
    Project string
    PulumiLabels map[string]string
    The combination of labels configured directly on the resource and default labels configured on the provider.
    State string
    Current state of the DataScan.
    Type string
    The type of DataScan.
    Uid string
    System generated globally unique ID for the scan. This ID will be different if the scan is deleted and re-created with the same name.
    UpdateTime string
    The time when the scan was last updated.
    createTime String
    The time when the scan was created.
    data DatascanData
    The data source for DataScan. Structure is documented below.
    dataProfileSpec DatascanDataProfileSpec
    DataProfileScan related setting.
    dataQualitySpec DatascanDataQualitySpec
    DataQualityScan related setting.
    dataScanId String
    DataScan identifier. Must contain only lowercase letters, numbers and hyphens. Must start with a letter. Must end with a number or a letter.
    description String
    Description of the scan.
    displayName String
    User friendly display name.
    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.
    executionSpec DatascanExecutionSpec
    DataScan execution settings. Structure is documented below.
    executionStatuses List<DatascanExecutionStatus>
    Status of the data scan execution. Structure is documented below.
    labels Map<String,String>
    User-defined labels for the scan. A list of key->value pairs. 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.
    location String
    The location where the data scan should reside.
    name String
    The relative resource name of the scan, of the form: projects/{project}/locations/{locationId}/dataScans/{datascan_id}, where project refers to a project_id or project_number and locationId refers to a GCP region.
    project String
    pulumiLabels Map<String,String>
    The combination of labels configured directly on the resource and default labels configured on the provider.
    state String
    Current state of the DataScan.
    type String
    The type of DataScan.
    uid String
    System generated globally unique ID for the scan. This ID will be different if the scan is deleted and re-created with the same name.
    updateTime String
    The time when the scan was last updated.
    createTime string
    The time when the scan was created.
    data DatascanData
    The data source for DataScan. Structure is documented below.
    dataProfileSpec DatascanDataProfileSpec
    DataProfileScan related setting.
    dataQualitySpec DatascanDataQualitySpec
    DataQualityScan related setting.
    dataScanId string
    DataScan identifier. Must contain only lowercase letters, numbers and hyphens. Must start with a letter. Must end with a number or a letter.
    description string
    Description of the scan.
    displayName string
    User friendly display name.
    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.
    executionSpec DatascanExecutionSpec
    DataScan execution settings. Structure is documented below.
    executionStatuses DatascanExecutionStatus[]
    Status of the data scan execution. Structure is documented below.
    labels {[key: string]: string}
    User-defined labels for the scan. A list of key->value pairs. 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.
    location string
    The location where the data scan should reside.
    name string
    The relative resource name of the scan, of the form: projects/{project}/locations/{locationId}/dataScans/{datascan_id}, where project refers to a project_id or project_number and locationId refers to a GCP region.
    project string
    pulumiLabels {[key: string]: string}
    The combination of labels configured directly on the resource and default labels configured on the provider.
    state string
    Current state of the DataScan.
    type string
    The type of DataScan.
    uid string
    System generated globally unique ID for the scan. This ID will be different if the scan is deleted and re-created with the same name.
    updateTime string
    The time when the scan was last updated.
    create_time str
    The time when the scan was created.
    data DatascanDataArgs
    The data source for DataScan. Structure is documented below.
    data_profile_spec DatascanDataProfileSpecArgs
    DataProfileScan related setting.
    data_quality_spec DatascanDataQualitySpecArgs
    DataQualityScan related setting.
    data_scan_id str
    DataScan identifier. Must contain only lowercase letters, numbers and hyphens. Must start with a letter. Must end with a number or a letter.
    description str
    Description of the scan.
    display_name str
    User friendly display name.
    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.
    execution_spec DatascanExecutionSpecArgs
    DataScan execution settings. Structure is documented below.
    execution_statuses Sequence[DatascanExecutionStatusArgs]
    Status of the data scan execution. Structure is documented below.
    labels Mapping[str, str]
    User-defined labels for the scan. A list of key->value pairs. 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.
    location str
    The location where the data scan should reside.
    name str
    The relative resource name of the scan, of the form: projects/{project}/locations/{locationId}/dataScans/{datascan_id}, where project refers to a project_id or project_number and locationId refers to a GCP region.
    project str
    pulumi_labels Mapping[str, str]
    The combination of labels configured directly on the resource and default labels configured on the provider.
    state str
    Current state of the DataScan.
    type str
    The type of DataScan.
    uid str
    System generated globally unique ID for the scan. This ID will be different if the scan is deleted and re-created with the same name.
    update_time str
    The time when the scan was last updated.
    createTime String
    The time when the scan was created.
    data Property Map
    The data source for DataScan. Structure is documented below.
    dataProfileSpec Property Map
    DataProfileScan related setting.
    dataQualitySpec Property Map
    DataQualityScan related setting.
    dataScanId String
    DataScan identifier. Must contain only lowercase letters, numbers and hyphens. Must start with a letter. Must end with a number or a letter.
    description String
    Description of the scan.
    displayName String
    User friendly display name.
    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.
    executionSpec Property Map
    DataScan execution settings. Structure is documented below.
    executionStatuses List<Property Map>
    Status of the data scan execution. Structure is documented below.
    labels Map<String>
    User-defined labels for the scan. A list of key->value pairs. 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.
    location String
    The location where the data scan should reside.
    name String
    The relative resource name of the scan, of the form: projects/{project}/locations/{locationId}/dataScans/{datascan_id}, where project refers to a project_id or project_number and locationId refers to a GCP region.
    project String
    pulumiLabels Map<String>
    The combination of labels configured directly on the resource and default labels configured on the provider.
    state String
    Current state of the DataScan.
    type String
    The type of DataScan.
    uid String
    System generated globally unique ID for the scan. This ID will be different if the scan is deleted and re-created with the same name.
    updateTime String
    The time when the scan was last updated.

    Supporting Types

    DatascanData, DatascanDataArgs

    Entity string
    The Dataplex entity that represents the data source(e.g. BigQuery table) for Datascan.
    Resource string
    The service-qualified full resource name of the cloud resource for a DataScan job to scan against. The field could be: (Cloud Storage bucket for DataDiscoveryScan)BigQuery table of type "TABLE" for DataProfileScan/DataQualityScan.
    Entity string
    The Dataplex entity that represents the data source(e.g. BigQuery table) for Datascan.
    Resource string
    The service-qualified full resource name of the cloud resource for a DataScan job to scan against. The field could be: (Cloud Storage bucket for DataDiscoveryScan)BigQuery table of type "TABLE" for DataProfileScan/DataQualityScan.
    entity String
    The Dataplex entity that represents the data source(e.g. BigQuery table) for Datascan.
    resource String
    The service-qualified full resource name of the cloud resource for a DataScan job to scan against. The field could be: (Cloud Storage bucket for DataDiscoveryScan)BigQuery table of type "TABLE" for DataProfileScan/DataQualityScan.
    entity string
    The Dataplex entity that represents the data source(e.g. BigQuery table) for Datascan.
    resource string
    The service-qualified full resource name of the cloud resource for a DataScan job to scan against. The field could be: (Cloud Storage bucket for DataDiscoveryScan)BigQuery table of type "TABLE" for DataProfileScan/DataQualityScan.
    entity str
    The Dataplex entity that represents the data source(e.g. BigQuery table) for Datascan.
    resource str
    The service-qualified full resource name of the cloud resource for a DataScan job to scan against. The field could be: (Cloud Storage bucket for DataDiscoveryScan)BigQuery table of type "TABLE" for DataProfileScan/DataQualityScan.
    entity String
    The Dataplex entity that represents the data source(e.g. BigQuery table) for Datascan.
    resource String
    The service-qualified full resource name of the cloud resource for a DataScan job to scan against. The field could be: (Cloud Storage bucket for DataDiscoveryScan)BigQuery table of type "TABLE" for DataProfileScan/DataQualityScan.

    DatascanDataProfileSpec, DatascanDataProfileSpecArgs

    ExcludeFields DatascanDataProfileSpecExcludeFields
    The fields to exclude from data profile. If specified, the fields will be excluded from data profile, regardless of include_fields value. Structure is documented below.
    IncludeFields DatascanDataProfileSpecIncludeFields
    The fields to include in data profile. If not specified, all fields at the time of profile scan job execution are included, except for ones listed in exclude_fields. Structure is documented below.
    PostScanActions DatascanDataProfileSpecPostScanActions
    Actions to take upon job completion. Structure is documented below.
    RowFilter string
    A filter applied to all rows in a single DataScan job. The filter needs to be a valid SQL expression for a WHERE clause in BigQuery standard SQL syntax. Example: col1 >= 0 AND col2 < 10
    SamplingPercent double
    The percentage of the records to be selected from the dataset for DataScan. Value can range between 0.0 and 100.0 with up to 3 significant decimal digits. Sampling is not applied if sampling_percent is not specified, 0 or 100.
    ExcludeFields DatascanDataProfileSpecExcludeFields
    The fields to exclude from data profile. If specified, the fields will be excluded from data profile, regardless of include_fields value. Structure is documented below.
    IncludeFields DatascanDataProfileSpecIncludeFields
    The fields to include in data profile. If not specified, all fields at the time of profile scan job execution are included, except for ones listed in exclude_fields. Structure is documented below.
    PostScanActions DatascanDataProfileSpecPostScanActions
    Actions to take upon job completion. Structure is documented below.
    RowFilter string
    A filter applied to all rows in a single DataScan job. The filter needs to be a valid SQL expression for a WHERE clause in BigQuery standard SQL syntax. Example: col1 >= 0 AND col2 < 10
    SamplingPercent float64
    The percentage of the records to be selected from the dataset for DataScan. Value can range between 0.0 and 100.0 with up to 3 significant decimal digits. Sampling is not applied if sampling_percent is not specified, 0 or 100.
    excludeFields DatascanDataProfileSpecExcludeFields
    The fields to exclude from data profile. If specified, the fields will be excluded from data profile, regardless of include_fields value. Structure is documented below.
    includeFields DatascanDataProfileSpecIncludeFields
    The fields to include in data profile. If not specified, all fields at the time of profile scan job execution are included, except for ones listed in exclude_fields. Structure is documented below.
    postScanActions DatascanDataProfileSpecPostScanActions
    Actions to take upon job completion. Structure is documented below.
    rowFilter String
    A filter applied to all rows in a single DataScan job. The filter needs to be a valid SQL expression for a WHERE clause in BigQuery standard SQL syntax. Example: col1 >= 0 AND col2 < 10
    samplingPercent Double
    The percentage of the records to be selected from the dataset for DataScan. Value can range between 0.0 and 100.0 with up to 3 significant decimal digits. Sampling is not applied if sampling_percent is not specified, 0 or 100.
    excludeFields DatascanDataProfileSpecExcludeFields
    The fields to exclude from data profile. If specified, the fields will be excluded from data profile, regardless of include_fields value. Structure is documented below.
    includeFields DatascanDataProfileSpecIncludeFields
    The fields to include in data profile. If not specified, all fields at the time of profile scan job execution are included, except for ones listed in exclude_fields. Structure is documented below.
    postScanActions DatascanDataProfileSpecPostScanActions
    Actions to take upon job completion. Structure is documented below.
    rowFilter string
    A filter applied to all rows in a single DataScan job. The filter needs to be a valid SQL expression for a WHERE clause in BigQuery standard SQL syntax. Example: col1 >= 0 AND col2 < 10
    samplingPercent number
    The percentage of the records to be selected from the dataset for DataScan. Value can range between 0.0 and 100.0 with up to 3 significant decimal digits. Sampling is not applied if sampling_percent is not specified, 0 or 100.
    exclude_fields DatascanDataProfileSpecExcludeFields
    The fields to exclude from data profile. If specified, the fields will be excluded from data profile, regardless of include_fields value. Structure is documented below.
    include_fields DatascanDataProfileSpecIncludeFields
    The fields to include in data profile. If not specified, all fields at the time of profile scan job execution are included, except for ones listed in exclude_fields. Structure is documented below.
    post_scan_actions DatascanDataProfileSpecPostScanActions
    Actions to take upon job completion. Structure is documented below.
    row_filter str
    A filter applied to all rows in a single DataScan job. The filter needs to be a valid SQL expression for a WHERE clause in BigQuery standard SQL syntax. Example: col1 >= 0 AND col2 < 10
    sampling_percent float
    The percentage of the records to be selected from the dataset for DataScan. Value can range between 0.0 and 100.0 with up to 3 significant decimal digits. Sampling is not applied if sampling_percent is not specified, 0 or 100.
    excludeFields Property Map
    The fields to exclude from data profile. If specified, the fields will be excluded from data profile, regardless of include_fields value. Structure is documented below.
    includeFields Property Map
    The fields to include in data profile. If not specified, all fields at the time of profile scan job execution are included, except for ones listed in exclude_fields. Structure is documented below.
    postScanActions Property Map
    Actions to take upon job completion. Structure is documented below.
    rowFilter String
    A filter applied to all rows in a single DataScan job. The filter needs to be a valid SQL expression for a WHERE clause in BigQuery standard SQL syntax. Example: col1 >= 0 AND col2 < 10
    samplingPercent Number
    The percentage of the records to be selected from the dataset for DataScan. Value can range between 0.0 and 100.0 with up to 3 significant decimal digits. Sampling is not applied if sampling_percent is not specified, 0 or 100.

    DatascanDataProfileSpecExcludeFields, DatascanDataProfileSpecExcludeFieldsArgs

    FieldNames List<string>
    Expected input is a list of fully qualified names of fields as in the schema. Only top-level field names for nested fields are supported. For instance, if 'x' is of nested field type, listing 'x' is supported but 'x.y.z' is not supported. Here 'y' and 'y.z' are nested fields of 'x'.
    FieldNames []string
    Expected input is a list of fully qualified names of fields as in the schema. Only top-level field names for nested fields are supported. For instance, if 'x' is of nested field type, listing 'x' is supported but 'x.y.z' is not supported. Here 'y' and 'y.z' are nested fields of 'x'.
    fieldNames List<String>
    Expected input is a list of fully qualified names of fields as in the schema. Only top-level field names for nested fields are supported. For instance, if 'x' is of nested field type, listing 'x' is supported but 'x.y.z' is not supported. Here 'y' and 'y.z' are nested fields of 'x'.
    fieldNames string[]
    Expected input is a list of fully qualified names of fields as in the schema. Only top-level field names for nested fields are supported. For instance, if 'x' is of nested field type, listing 'x' is supported but 'x.y.z' is not supported. Here 'y' and 'y.z' are nested fields of 'x'.
    field_names Sequence[str]
    Expected input is a list of fully qualified names of fields as in the schema. Only top-level field names for nested fields are supported. For instance, if 'x' is of nested field type, listing 'x' is supported but 'x.y.z' is not supported. Here 'y' and 'y.z' are nested fields of 'x'.
    fieldNames List<String>
    Expected input is a list of fully qualified names of fields as in the schema. Only top-level field names for nested fields are supported. For instance, if 'x' is of nested field type, listing 'x' is supported but 'x.y.z' is not supported. Here 'y' and 'y.z' are nested fields of 'x'.

    DatascanDataProfileSpecIncludeFields, DatascanDataProfileSpecIncludeFieldsArgs

    FieldNames List<string>
    Expected input is a list of fully qualified names of fields as in the schema. Only top-level field names for nested fields are supported. For instance, if 'x' is of nested field type, listing 'x' is supported but 'x.y.z' is not supported. Here 'y' and 'y.z' are nested fields of 'x'.
    FieldNames []string
    Expected input is a list of fully qualified names of fields as in the schema. Only top-level field names for nested fields are supported. For instance, if 'x' is of nested field type, listing 'x' is supported but 'x.y.z' is not supported. Here 'y' and 'y.z' are nested fields of 'x'.
    fieldNames List<String>
    Expected input is a list of fully qualified names of fields as in the schema. Only top-level field names for nested fields are supported. For instance, if 'x' is of nested field type, listing 'x' is supported but 'x.y.z' is not supported. Here 'y' and 'y.z' are nested fields of 'x'.
    fieldNames string[]
    Expected input is a list of fully qualified names of fields as in the schema. Only top-level field names for nested fields are supported. For instance, if 'x' is of nested field type, listing 'x' is supported but 'x.y.z' is not supported. Here 'y' and 'y.z' are nested fields of 'x'.
    field_names Sequence[str]
    Expected input is a list of fully qualified names of fields as in the schema. Only top-level field names for nested fields are supported. For instance, if 'x' is of nested field type, listing 'x' is supported but 'x.y.z' is not supported. Here 'y' and 'y.z' are nested fields of 'x'.
    fieldNames List<String>
    Expected input is a list of fully qualified names of fields as in the schema. Only top-level field names for nested fields are supported. For instance, if 'x' is of nested field type, listing 'x' is supported but 'x.y.z' is not supported. Here 'y' and 'y.z' are nested fields of 'x'.

    DatascanDataProfileSpecPostScanActions, DatascanDataProfileSpecPostScanActionsArgs

    BigqueryExport DatascanDataProfileSpecPostScanActionsBigqueryExport
    If set, results will be exported to the provided BigQuery table. Structure is documented below.
    BigqueryExport DatascanDataProfileSpecPostScanActionsBigqueryExport
    If set, results will be exported to the provided BigQuery table. Structure is documented below.
    bigqueryExport DatascanDataProfileSpecPostScanActionsBigqueryExport
    If set, results will be exported to the provided BigQuery table. Structure is documented below.
    bigqueryExport DatascanDataProfileSpecPostScanActionsBigqueryExport
    If set, results will be exported to the provided BigQuery table. Structure is documented below.
    bigquery_export DatascanDataProfileSpecPostScanActionsBigqueryExport
    If set, results will be exported to the provided BigQuery table. Structure is documented below.
    bigqueryExport Property Map
    If set, results will be exported to the provided BigQuery table. Structure is documented below.

    DatascanDataProfileSpecPostScanActionsBigqueryExport, DatascanDataProfileSpecPostScanActionsBigqueryExportArgs

    ResultsTable string
    The BigQuery table to export DataProfileScan results to. Format://bigquery.googleapis.com/projects/PROJECT_ID/datasets/DATASET_ID/tables/TABLE_ID
    ResultsTable string
    The BigQuery table to export DataProfileScan results to. Format://bigquery.googleapis.com/projects/PROJECT_ID/datasets/DATASET_ID/tables/TABLE_ID
    resultsTable String
    The BigQuery table to export DataProfileScan results to. Format://bigquery.googleapis.com/projects/PROJECT_ID/datasets/DATASET_ID/tables/TABLE_ID
    resultsTable string
    The BigQuery table to export DataProfileScan results to. Format://bigquery.googleapis.com/projects/PROJECT_ID/datasets/DATASET_ID/tables/TABLE_ID
    results_table str
    The BigQuery table to export DataProfileScan results to. Format://bigquery.googleapis.com/projects/PROJECT_ID/datasets/DATASET_ID/tables/TABLE_ID
    resultsTable String
    The BigQuery table to export DataProfileScan results to. Format://bigquery.googleapis.com/projects/PROJECT_ID/datasets/DATASET_ID/tables/TABLE_ID

    DatascanDataQualitySpec, DatascanDataQualitySpecArgs

    PostScanActions DatascanDataQualitySpecPostScanActions
    Actions to take upon job completion. Structure is documented below.
    RowFilter string
    A filter applied to all rows in a single DataScan job. The filter needs to be a valid SQL expression for a WHERE clause in BigQuery standard SQL syntax. Example: col1 >= 0 AND col2 < 10
    Rules List<DatascanDataQualitySpecRule>
    The list of rules to evaluate against a data source. At least one rule is required. Structure is documented below.
    SamplingPercent double
    The percentage of the records to be selected from the dataset for DataScan. Value can range between 0.0 and 100.0 with up to 3 significant decimal digits. Sampling is not applied if sampling_percent is not specified, 0 or 100.
    PostScanActions DatascanDataQualitySpecPostScanActions
    Actions to take upon job completion. Structure is documented below.
    RowFilter string
    A filter applied to all rows in a single DataScan job. The filter needs to be a valid SQL expression for a WHERE clause in BigQuery standard SQL syntax. Example: col1 >= 0 AND col2 < 10
    Rules []DatascanDataQualitySpecRule
    The list of rules to evaluate against a data source. At least one rule is required. Structure is documented below.
    SamplingPercent float64
    The percentage of the records to be selected from the dataset for DataScan. Value can range between 0.0 and 100.0 with up to 3 significant decimal digits. Sampling is not applied if sampling_percent is not specified, 0 or 100.
    postScanActions DatascanDataQualitySpecPostScanActions
    Actions to take upon job completion. Structure is documented below.
    rowFilter String
    A filter applied to all rows in a single DataScan job. The filter needs to be a valid SQL expression for a WHERE clause in BigQuery standard SQL syntax. Example: col1 >= 0 AND col2 < 10
    rules List<DatascanDataQualitySpecRule>
    The list of rules to evaluate against a data source. At least one rule is required. Structure is documented below.
    samplingPercent Double
    The percentage of the records to be selected from the dataset for DataScan. Value can range between 0.0 and 100.0 with up to 3 significant decimal digits. Sampling is not applied if sampling_percent is not specified, 0 or 100.
    postScanActions DatascanDataQualitySpecPostScanActions
    Actions to take upon job completion. Structure is documented below.
    rowFilter string
    A filter applied to all rows in a single DataScan job. The filter needs to be a valid SQL expression for a WHERE clause in BigQuery standard SQL syntax. Example: col1 >= 0 AND col2 < 10
    rules DatascanDataQualitySpecRule[]
    The list of rules to evaluate against a data source. At least one rule is required. Structure is documented below.
    samplingPercent number
    The percentage of the records to be selected from the dataset for DataScan. Value can range between 0.0 and 100.0 with up to 3 significant decimal digits. Sampling is not applied if sampling_percent is not specified, 0 or 100.
    post_scan_actions DatascanDataQualitySpecPostScanActions
    Actions to take upon job completion. Structure is documented below.
    row_filter str
    A filter applied to all rows in a single DataScan job. The filter needs to be a valid SQL expression for a WHERE clause in BigQuery standard SQL syntax. Example: col1 >= 0 AND col2 < 10
    rules Sequence[DatascanDataQualitySpecRule]
    The list of rules to evaluate against a data source. At least one rule is required. Structure is documented below.
    sampling_percent float
    The percentage of the records to be selected from the dataset for DataScan. Value can range between 0.0 and 100.0 with up to 3 significant decimal digits. Sampling is not applied if sampling_percent is not specified, 0 or 100.
    postScanActions Property Map
    Actions to take upon job completion. Structure is documented below.
    rowFilter String
    A filter applied to all rows in a single DataScan job. The filter needs to be a valid SQL expression for a WHERE clause in BigQuery standard SQL syntax. Example: col1 >= 0 AND col2 < 10
    rules List<Property Map>
    The list of rules to evaluate against a data source. At least one rule is required. Structure is documented below.
    samplingPercent Number
    The percentage of the records to be selected from the dataset for DataScan. Value can range between 0.0 and 100.0 with up to 3 significant decimal digits. Sampling is not applied if sampling_percent is not specified, 0 or 100.

    DatascanDataQualitySpecPostScanActions, DatascanDataQualitySpecPostScanActionsArgs

    BigqueryExport DatascanDataQualitySpecPostScanActionsBigqueryExport
    If set, results will be exported to the provided BigQuery table. Structure is documented below.
    BigqueryExport DatascanDataQualitySpecPostScanActionsBigqueryExport
    If set, results will be exported to the provided BigQuery table. Structure is documented below.
    bigqueryExport DatascanDataQualitySpecPostScanActionsBigqueryExport
    If set, results will be exported to the provided BigQuery table. Structure is documented below.
    bigqueryExport DatascanDataQualitySpecPostScanActionsBigqueryExport
    If set, results will be exported to the provided BigQuery table. Structure is documented below.
    bigquery_export DatascanDataQualitySpecPostScanActionsBigqueryExport
    If set, results will be exported to the provided BigQuery table. Structure is documented below.
    bigqueryExport Property Map
    If set, results will be exported to the provided BigQuery table. Structure is documented below.

    DatascanDataQualitySpecPostScanActionsBigqueryExport, DatascanDataQualitySpecPostScanActionsBigqueryExportArgs

    ResultsTable string
    The BigQuery table to export DataProfileScan results to. Format://bigquery.googleapis.com/projects/PROJECT_ID/datasets/DATASET_ID/tables/TABLE_ID
    ResultsTable string
    The BigQuery table to export DataProfileScan results to. Format://bigquery.googleapis.com/projects/PROJECT_ID/datasets/DATASET_ID/tables/TABLE_ID
    resultsTable String
    The BigQuery table to export DataProfileScan results to. Format://bigquery.googleapis.com/projects/PROJECT_ID/datasets/DATASET_ID/tables/TABLE_ID
    resultsTable string
    The BigQuery table to export DataProfileScan results to. Format://bigquery.googleapis.com/projects/PROJECT_ID/datasets/DATASET_ID/tables/TABLE_ID
    results_table str
    The BigQuery table to export DataProfileScan results to. Format://bigquery.googleapis.com/projects/PROJECT_ID/datasets/DATASET_ID/tables/TABLE_ID
    resultsTable String
    The BigQuery table to export DataProfileScan results to. Format://bigquery.googleapis.com/projects/PROJECT_ID/datasets/DATASET_ID/tables/TABLE_ID

    DatascanDataQualitySpecRule, DatascanDataQualitySpecRuleArgs

    Dimension string
    The dimension a rule belongs to. Results are also aggregated at the dimension level. Supported dimensions are ["COMPLETENESS", "ACCURACY", "CONSISTENCY", "VALIDITY", "UNIQUENESS", "INTEGRITY"]
    Column string
    The unnested column which this rule is evaluated against.
    Description string
    Description of the rule. The maximum length is 1,024 characters.
    IgnoreNull bool
    Rows with null values will automatically fail a rule, unless ignoreNull is true. In that case, such null rows are trivially considered passing. Only applicable to ColumnMap rules.
    Name string
    A mutable name for the rule. The name must contain only letters (a-z, A-Z), numbers (0-9), or hyphens (-). The maximum length is 63 characters. Must start with a letter. Must end with a number or a letter.
    NonNullExpectation DatascanDataQualitySpecRuleNonNullExpectation
    ColumnMap rule which evaluates whether each column value is null.
    RangeExpectation DatascanDataQualitySpecRuleRangeExpectation
    ColumnMap rule which evaluates whether each column value lies between a specified range. Structure is documented below.
    RegexExpectation DatascanDataQualitySpecRuleRegexExpectation
    ColumnMap rule which evaluates whether each column value matches a specified regex. Structure is documented below.
    RowConditionExpectation DatascanDataQualitySpecRuleRowConditionExpectation
    Table rule which evaluates whether each row passes the specified condition. Structure is documented below.
    SetExpectation DatascanDataQualitySpecRuleSetExpectation
    ColumnMap rule which evaluates whether each column value is contained by a specified set. Structure is documented below.
    StatisticRangeExpectation DatascanDataQualitySpecRuleStatisticRangeExpectation
    ColumnAggregate rule which evaluates whether the column aggregate statistic lies between a specified range. Structure is documented below.
    TableConditionExpectation DatascanDataQualitySpecRuleTableConditionExpectation
    Table rule which evaluates whether the provided expression is true. Structure is documented below.
    Threshold double
    The minimum ratio of passing_rows / total_rows required to pass this rule, with a range of [0.0, 1.0]. 0 indicates default value (i.e. 1.0).
    UniquenessExpectation DatascanDataQualitySpecRuleUniquenessExpectation
    Row-level rule which evaluates whether each column value is unique.
    Dimension string
    The dimension a rule belongs to. Results are also aggregated at the dimension level. Supported dimensions are ["COMPLETENESS", "ACCURACY", "CONSISTENCY", "VALIDITY", "UNIQUENESS", "INTEGRITY"]
    Column string
    The unnested column which this rule is evaluated against.
    Description string
    Description of the rule. The maximum length is 1,024 characters.
    IgnoreNull bool
    Rows with null values will automatically fail a rule, unless ignoreNull is true. In that case, such null rows are trivially considered passing. Only applicable to ColumnMap rules.
    Name string
    A mutable name for the rule. The name must contain only letters (a-z, A-Z), numbers (0-9), or hyphens (-). The maximum length is 63 characters. Must start with a letter. Must end with a number or a letter.
    NonNullExpectation DatascanDataQualitySpecRuleNonNullExpectation
    ColumnMap rule which evaluates whether each column value is null.
    RangeExpectation DatascanDataQualitySpecRuleRangeExpectation
    ColumnMap rule which evaluates whether each column value lies between a specified range. Structure is documented below.
    RegexExpectation DatascanDataQualitySpecRuleRegexExpectation
    ColumnMap rule which evaluates whether each column value matches a specified regex. Structure is documented below.
    RowConditionExpectation DatascanDataQualitySpecRuleRowConditionExpectation
    Table rule which evaluates whether each row passes the specified condition. Structure is documented below.
    SetExpectation DatascanDataQualitySpecRuleSetExpectation
    ColumnMap rule which evaluates whether each column value is contained by a specified set. Structure is documented below.
    StatisticRangeExpectation DatascanDataQualitySpecRuleStatisticRangeExpectation
    ColumnAggregate rule which evaluates whether the column aggregate statistic lies between a specified range. Structure is documented below.
    TableConditionExpectation DatascanDataQualitySpecRuleTableConditionExpectation
    Table rule which evaluates whether the provided expression is true. Structure is documented below.
    Threshold float64
    The minimum ratio of passing_rows / total_rows required to pass this rule, with a range of [0.0, 1.0]. 0 indicates default value (i.e. 1.0).
    UniquenessExpectation DatascanDataQualitySpecRuleUniquenessExpectation
    Row-level rule which evaluates whether each column value is unique.
    dimension String
    The dimension a rule belongs to. Results are also aggregated at the dimension level. Supported dimensions are ["COMPLETENESS", "ACCURACY", "CONSISTENCY", "VALIDITY", "UNIQUENESS", "INTEGRITY"]
    column String
    The unnested column which this rule is evaluated against.
    description String
    Description of the rule. The maximum length is 1,024 characters.
    ignoreNull Boolean
    Rows with null values will automatically fail a rule, unless ignoreNull is true. In that case, such null rows are trivially considered passing. Only applicable to ColumnMap rules.
    name String
    A mutable name for the rule. The name must contain only letters (a-z, A-Z), numbers (0-9), or hyphens (-). The maximum length is 63 characters. Must start with a letter. Must end with a number or a letter.
    nonNullExpectation DatascanDataQualitySpecRuleNonNullExpectation
    ColumnMap rule which evaluates whether each column value is null.
    rangeExpectation DatascanDataQualitySpecRuleRangeExpectation
    ColumnMap rule which evaluates whether each column value lies between a specified range. Structure is documented below.
    regexExpectation DatascanDataQualitySpecRuleRegexExpectation
    ColumnMap rule which evaluates whether each column value matches a specified regex. Structure is documented below.
    rowConditionExpectation DatascanDataQualitySpecRuleRowConditionExpectation
    Table rule which evaluates whether each row passes the specified condition. Structure is documented below.
    setExpectation DatascanDataQualitySpecRuleSetExpectation
    ColumnMap rule which evaluates whether each column value is contained by a specified set. Structure is documented below.
    statisticRangeExpectation DatascanDataQualitySpecRuleStatisticRangeExpectation
    ColumnAggregate rule which evaluates whether the column aggregate statistic lies between a specified range. Structure is documented below.
    tableConditionExpectation DatascanDataQualitySpecRuleTableConditionExpectation
    Table rule which evaluates whether the provided expression is true. Structure is documented below.
    threshold Double
    The minimum ratio of passing_rows / total_rows required to pass this rule, with a range of [0.0, 1.0]. 0 indicates default value (i.e. 1.0).
    uniquenessExpectation DatascanDataQualitySpecRuleUniquenessExpectation
    Row-level rule which evaluates whether each column value is unique.
    dimension string
    The dimension a rule belongs to. Results are also aggregated at the dimension level. Supported dimensions are ["COMPLETENESS", "ACCURACY", "CONSISTENCY", "VALIDITY", "UNIQUENESS", "INTEGRITY"]
    column string
    The unnested column which this rule is evaluated against.
    description string
    Description of the rule. The maximum length is 1,024 characters.
    ignoreNull boolean
    Rows with null values will automatically fail a rule, unless ignoreNull is true. In that case, such null rows are trivially considered passing. Only applicable to ColumnMap rules.
    name string
    A mutable name for the rule. The name must contain only letters (a-z, A-Z), numbers (0-9), or hyphens (-). The maximum length is 63 characters. Must start with a letter. Must end with a number or a letter.
    nonNullExpectation DatascanDataQualitySpecRuleNonNullExpectation
    ColumnMap rule which evaluates whether each column value is null.
    rangeExpectation DatascanDataQualitySpecRuleRangeExpectation
    ColumnMap rule which evaluates whether each column value lies between a specified range. Structure is documented below.
    regexExpectation DatascanDataQualitySpecRuleRegexExpectation
    ColumnMap rule which evaluates whether each column value matches a specified regex. Structure is documented below.
    rowConditionExpectation DatascanDataQualitySpecRuleRowConditionExpectation
    Table rule which evaluates whether each row passes the specified condition. Structure is documented below.
    setExpectation DatascanDataQualitySpecRuleSetExpectation
    ColumnMap rule which evaluates whether each column value is contained by a specified set. Structure is documented below.
    statisticRangeExpectation DatascanDataQualitySpecRuleStatisticRangeExpectation
    ColumnAggregate rule which evaluates whether the column aggregate statistic lies between a specified range. Structure is documented below.
    tableConditionExpectation DatascanDataQualitySpecRuleTableConditionExpectation
    Table rule which evaluates whether the provided expression is true. Structure is documented below.
    threshold number
    The minimum ratio of passing_rows / total_rows required to pass this rule, with a range of [0.0, 1.0]. 0 indicates default value (i.e. 1.0).
    uniquenessExpectation DatascanDataQualitySpecRuleUniquenessExpectation
    Row-level rule which evaluates whether each column value is unique.
    dimension str
    The dimension a rule belongs to. Results are also aggregated at the dimension level. Supported dimensions are ["COMPLETENESS", "ACCURACY", "CONSISTENCY", "VALIDITY", "UNIQUENESS", "INTEGRITY"]
    column str
    The unnested column which this rule is evaluated against.
    description str
    Description of the rule. The maximum length is 1,024 characters.
    ignore_null bool
    Rows with null values will automatically fail a rule, unless ignoreNull is true. In that case, such null rows are trivially considered passing. Only applicable to ColumnMap rules.
    name str
    A mutable name for the rule. The name must contain only letters (a-z, A-Z), numbers (0-9), or hyphens (-). The maximum length is 63 characters. Must start with a letter. Must end with a number or a letter.
    non_null_expectation DatascanDataQualitySpecRuleNonNullExpectation
    ColumnMap rule which evaluates whether each column value is null.
    range_expectation DatascanDataQualitySpecRuleRangeExpectation
    ColumnMap rule which evaluates whether each column value lies between a specified range. Structure is documented below.
    regex_expectation DatascanDataQualitySpecRuleRegexExpectation
    ColumnMap rule which evaluates whether each column value matches a specified regex. Structure is documented below.
    row_condition_expectation DatascanDataQualitySpecRuleRowConditionExpectation
    Table rule which evaluates whether each row passes the specified condition. Structure is documented below.
    set_expectation DatascanDataQualitySpecRuleSetExpectation
    ColumnMap rule which evaluates whether each column value is contained by a specified set. Structure is documented below.
    statistic_range_expectation DatascanDataQualitySpecRuleStatisticRangeExpectation
    ColumnAggregate rule which evaluates whether the column aggregate statistic lies between a specified range. Structure is documented below.
    table_condition_expectation DatascanDataQualitySpecRuleTableConditionExpectation
    Table rule which evaluates whether the provided expression is true. Structure is documented below.
    threshold float
    The minimum ratio of passing_rows / total_rows required to pass this rule, with a range of [0.0, 1.0]. 0 indicates default value (i.e. 1.0).
    uniqueness_expectation DatascanDataQualitySpecRuleUniquenessExpectation
    Row-level rule which evaluates whether each column value is unique.
    dimension String
    The dimension a rule belongs to. Results are also aggregated at the dimension level. Supported dimensions are ["COMPLETENESS", "ACCURACY", "CONSISTENCY", "VALIDITY", "UNIQUENESS", "INTEGRITY"]
    column String
    The unnested column which this rule is evaluated against.
    description String
    Description of the rule. The maximum length is 1,024 characters.
    ignoreNull Boolean
    Rows with null values will automatically fail a rule, unless ignoreNull is true. In that case, such null rows are trivially considered passing. Only applicable to ColumnMap rules.
    name String
    A mutable name for the rule. The name must contain only letters (a-z, A-Z), numbers (0-9), or hyphens (-). The maximum length is 63 characters. Must start with a letter. Must end with a number or a letter.
    nonNullExpectation Property Map
    ColumnMap rule which evaluates whether each column value is null.
    rangeExpectation Property Map
    ColumnMap rule which evaluates whether each column value lies between a specified range. Structure is documented below.
    regexExpectation Property Map
    ColumnMap rule which evaluates whether each column value matches a specified regex. Structure is documented below.
    rowConditionExpectation Property Map
    Table rule which evaluates whether each row passes the specified condition. Structure is documented below.
    setExpectation Property Map
    ColumnMap rule which evaluates whether each column value is contained by a specified set. Structure is documented below.
    statisticRangeExpectation Property Map
    ColumnAggregate rule which evaluates whether the column aggregate statistic lies between a specified range. Structure is documented below.
    tableConditionExpectation Property Map
    Table rule which evaluates whether the provided expression is true. Structure is documented below.
    threshold Number
    The minimum ratio of passing_rows / total_rows required to pass this rule, with a range of [0.0, 1.0]. 0 indicates default value (i.e. 1.0).
    uniquenessExpectation Property Map
    Row-level rule which evaluates whether each column value is unique.

    DatascanDataQualitySpecRuleRangeExpectation, DatascanDataQualitySpecRuleRangeExpectationArgs

    MaxValue string
    The maximum column value allowed for a row to pass this validation. At least one of minValue and maxValue need to be provided.
    MinValue string
    The minimum column value allowed for a row to pass this validation. At least one of minValue and maxValue need to be provided.
    StrictMaxEnabled bool
    Whether each value needs to be strictly lesser than ('<') the maximum, or if equality is allowed. Only relevant if a maxValue has been defined. Default = false.
    StrictMinEnabled bool
    Whether each value needs to be strictly greater than ('>') the minimum, or if equality is allowed. Only relevant if a minValue has been defined. Default = false.
    MaxValue string
    The maximum column value allowed for a row to pass this validation. At least one of minValue and maxValue need to be provided.
    MinValue string
    The minimum column value allowed for a row to pass this validation. At least one of minValue and maxValue need to be provided.
    StrictMaxEnabled bool
    Whether each value needs to be strictly lesser than ('<') the maximum, or if equality is allowed. Only relevant if a maxValue has been defined. Default = false.
    StrictMinEnabled bool
    Whether each value needs to be strictly greater than ('>') the minimum, or if equality is allowed. Only relevant if a minValue has been defined. Default = false.
    maxValue String
    The maximum column value allowed for a row to pass this validation. At least one of minValue and maxValue need to be provided.
    minValue String
    The minimum column value allowed for a row to pass this validation. At least one of minValue and maxValue need to be provided.
    strictMaxEnabled Boolean
    Whether each value needs to be strictly lesser than ('<') the maximum, or if equality is allowed. Only relevant if a maxValue has been defined. Default = false.
    strictMinEnabled Boolean
    Whether each value needs to be strictly greater than ('>') the minimum, or if equality is allowed. Only relevant if a minValue has been defined. Default = false.
    maxValue string
    The maximum column value allowed for a row to pass this validation. At least one of minValue and maxValue need to be provided.
    minValue string
    The minimum column value allowed for a row to pass this validation. At least one of minValue and maxValue need to be provided.
    strictMaxEnabled boolean
    Whether each value needs to be strictly lesser than ('<') the maximum, or if equality is allowed. Only relevant if a maxValue has been defined. Default = false.
    strictMinEnabled boolean
    Whether each value needs to be strictly greater than ('>') the minimum, or if equality is allowed. Only relevant if a minValue has been defined. Default = false.
    max_value str
    The maximum column value allowed for a row to pass this validation. At least one of minValue and maxValue need to be provided.
    min_value str
    The minimum column value allowed for a row to pass this validation. At least one of minValue and maxValue need to be provided.
    strict_max_enabled bool
    Whether each value needs to be strictly lesser than ('<') the maximum, or if equality is allowed. Only relevant if a maxValue has been defined. Default = false.
    strict_min_enabled bool
    Whether each value needs to be strictly greater than ('>') the minimum, or if equality is allowed. Only relevant if a minValue has been defined. Default = false.
    maxValue String
    The maximum column value allowed for a row to pass this validation. At least one of minValue and maxValue need to be provided.
    minValue String
    The minimum column value allowed for a row to pass this validation. At least one of minValue and maxValue need to be provided.
    strictMaxEnabled Boolean
    Whether each value needs to be strictly lesser than ('<') the maximum, or if equality is allowed. Only relevant if a maxValue has been defined. Default = false.
    strictMinEnabled Boolean
    Whether each value needs to be strictly greater than ('>') the minimum, or if equality is allowed. Only relevant if a minValue has been defined. Default = false.

    DatascanDataQualitySpecRuleRegexExpectation, DatascanDataQualitySpecRuleRegexExpectationArgs

    Regex string
    A regular expression the column value is expected to match.
    Regex string
    A regular expression the column value is expected to match.
    regex String
    A regular expression the column value is expected to match.
    regex string
    A regular expression the column value is expected to match.
    regex str
    A regular expression the column value is expected to match.
    regex String
    A regular expression the column value is expected to match.

    DatascanDataQualitySpecRuleRowConditionExpectation, DatascanDataQualitySpecRuleRowConditionExpectationArgs

    SqlExpression string
    The SQL expression.
    SqlExpression string
    The SQL expression.
    sqlExpression String
    The SQL expression.
    sqlExpression string
    The SQL expression.
    sql_expression str
    The SQL expression.
    sqlExpression String
    The SQL expression.

    DatascanDataQualitySpecRuleSetExpectation, DatascanDataQualitySpecRuleSetExpectationArgs

    Values List<string>
    Expected values for the column value.
    Values []string
    Expected values for the column value.
    values List<String>
    Expected values for the column value.
    values string[]
    Expected values for the column value.
    values Sequence[str]
    Expected values for the column value.
    values List<String>
    Expected values for the column value.

    DatascanDataQualitySpecRuleStatisticRangeExpectation, DatascanDataQualitySpecRuleStatisticRangeExpectationArgs

    Statistic string
    column statistics. Possible values are: STATISTIC_UNDEFINED, MEAN, MIN, MAX.
    MaxValue string
    The maximum column statistic value allowed for a row to pass this validation. At least one of minValue and maxValue need to be provided.
    MinValue string
    The minimum column statistic value allowed for a row to pass this validation. At least one of minValue and maxValue need to be provided.
    StrictMaxEnabled bool
    Whether column statistic needs to be strictly lesser than ('<') the maximum, or if equality is allowed. Only relevant if a maxValue has been defined. Default = false.
    StrictMinEnabled bool
    Whether column statistic needs to be strictly greater than ('>') the minimum, or if equality is allowed. Only relevant if a minValue has been defined. Default = false.
    Statistic string
    column statistics. Possible values are: STATISTIC_UNDEFINED, MEAN, MIN, MAX.
    MaxValue string
    The maximum column statistic value allowed for a row to pass this validation. At least one of minValue and maxValue need to be provided.
    MinValue string
    The minimum column statistic value allowed for a row to pass this validation. At least one of minValue and maxValue need to be provided.
    StrictMaxEnabled bool
    Whether column statistic needs to be strictly lesser than ('<') the maximum, or if equality is allowed. Only relevant if a maxValue has been defined. Default = false.
    StrictMinEnabled bool
    Whether column statistic needs to be strictly greater than ('>') the minimum, or if equality is allowed. Only relevant if a minValue has been defined. Default = false.
    statistic String
    column statistics. Possible values are: STATISTIC_UNDEFINED, MEAN, MIN, MAX.
    maxValue String
    The maximum column statistic value allowed for a row to pass this validation. At least one of minValue and maxValue need to be provided.
    minValue String
    The minimum column statistic value allowed for a row to pass this validation. At least one of minValue and maxValue need to be provided.
    strictMaxEnabled Boolean
    Whether column statistic needs to be strictly lesser than ('<') the maximum, or if equality is allowed. Only relevant if a maxValue has been defined. Default = false.
    strictMinEnabled Boolean
    Whether column statistic needs to be strictly greater than ('>') the minimum, or if equality is allowed. Only relevant if a minValue has been defined. Default = false.
    statistic string
    column statistics. Possible values are: STATISTIC_UNDEFINED, MEAN, MIN, MAX.
    maxValue string
    The maximum column statistic value allowed for a row to pass this validation. At least one of minValue and maxValue need to be provided.
    minValue string
    The minimum column statistic value allowed for a row to pass this validation. At least one of minValue and maxValue need to be provided.
    strictMaxEnabled boolean
    Whether column statistic needs to be strictly lesser than ('<') the maximum, or if equality is allowed. Only relevant if a maxValue has been defined. Default = false.
    strictMinEnabled boolean
    Whether column statistic needs to be strictly greater than ('>') the minimum, or if equality is allowed. Only relevant if a minValue has been defined. Default = false.
    statistic str
    column statistics. Possible values are: STATISTIC_UNDEFINED, MEAN, MIN, MAX.
    max_value str
    The maximum column statistic value allowed for a row to pass this validation. At least one of minValue and maxValue need to be provided.
    min_value str
    The minimum column statistic value allowed for a row to pass this validation. At least one of minValue and maxValue need to be provided.
    strict_max_enabled bool
    Whether column statistic needs to be strictly lesser than ('<') the maximum, or if equality is allowed. Only relevant if a maxValue has been defined. Default = false.
    strict_min_enabled bool
    Whether column statistic needs to be strictly greater than ('>') the minimum, or if equality is allowed. Only relevant if a minValue has been defined. Default = false.
    statistic String
    column statistics. Possible values are: STATISTIC_UNDEFINED, MEAN, MIN, MAX.
    maxValue String
    The maximum column statistic value allowed for a row to pass this validation. At least one of minValue and maxValue need to be provided.
    minValue String
    The minimum column statistic value allowed for a row to pass this validation. At least one of minValue and maxValue need to be provided.
    strictMaxEnabled Boolean
    Whether column statistic needs to be strictly lesser than ('<') the maximum, or if equality is allowed. Only relevant if a maxValue has been defined. Default = false.
    strictMinEnabled Boolean
    Whether column statistic needs to be strictly greater than ('>') the minimum, or if equality is allowed. Only relevant if a minValue has been defined. Default = false.

    DatascanDataQualitySpecRuleTableConditionExpectation, DatascanDataQualitySpecRuleTableConditionExpectationArgs

    SqlExpression string
    The SQL expression.
    SqlExpression string
    The SQL expression.
    sqlExpression String
    The SQL expression.
    sqlExpression string
    The SQL expression.
    sql_expression str
    The SQL expression.
    sqlExpression String
    The SQL expression.

    DatascanExecutionSpec, DatascanExecutionSpecArgs

    Trigger DatascanExecutionSpecTrigger
    Spec related to how often and when a scan should be triggered. Structure is documented below.
    Field string
    The unnested field (of type Date or Timestamp) that contains values which monotonically increase over time. If not specified, a data scan will run for all data in the table.
    Trigger DatascanExecutionSpecTrigger
    Spec related to how often and when a scan should be triggered. Structure is documented below.
    Field string
    The unnested field (of type Date or Timestamp) that contains values which monotonically increase over time. If not specified, a data scan will run for all data in the table.
    trigger DatascanExecutionSpecTrigger
    Spec related to how often and when a scan should be triggered. Structure is documented below.
    field String
    The unnested field (of type Date or Timestamp) that contains values which monotonically increase over time. If not specified, a data scan will run for all data in the table.
    trigger DatascanExecutionSpecTrigger
    Spec related to how often and when a scan should be triggered. Structure is documented below.
    field string
    The unnested field (of type Date or Timestamp) that contains values which monotonically increase over time. If not specified, a data scan will run for all data in the table.
    trigger DatascanExecutionSpecTrigger
    Spec related to how often and when a scan should be triggered. Structure is documented below.
    field str
    The unnested field (of type Date or Timestamp) that contains values which monotonically increase over time. If not specified, a data scan will run for all data in the table.
    trigger Property Map
    Spec related to how often and when a scan should be triggered. Structure is documented below.
    field String
    The unnested field (of type Date or Timestamp) that contains values which monotonically increase over time. If not specified, a data scan will run for all data in the table.

    DatascanExecutionSpecTrigger, DatascanExecutionSpecTriggerArgs

    OnDemand DatascanExecutionSpecTriggerOnDemand
    The scan runs once via dataScans.run API.
    Schedule DatascanExecutionSpecTriggerSchedule
    The scan is scheduled to run periodically. Structure is documented below.
    OnDemand DatascanExecutionSpecTriggerOnDemand
    The scan runs once via dataScans.run API.
    Schedule DatascanExecutionSpecTriggerSchedule
    The scan is scheduled to run periodically. Structure is documented below.
    onDemand DatascanExecutionSpecTriggerOnDemand
    The scan runs once via dataScans.run API.
    schedule DatascanExecutionSpecTriggerSchedule
    The scan is scheduled to run periodically. Structure is documented below.
    onDemand DatascanExecutionSpecTriggerOnDemand
    The scan runs once via dataScans.run API.
    schedule DatascanExecutionSpecTriggerSchedule
    The scan is scheduled to run periodically. Structure is documented below.
    on_demand DatascanExecutionSpecTriggerOnDemand
    The scan runs once via dataScans.run API.
    schedule DatascanExecutionSpecTriggerSchedule
    The scan is scheduled to run periodically. Structure is documented below.
    onDemand Property Map
    The scan runs once via dataScans.run API.
    schedule Property Map
    The scan is scheduled to run periodically. Structure is documented below.

    DatascanExecutionSpecTriggerSchedule, DatascanExecutionSpecTriggerScheduleArgs

    Cron string
    Cron schedule for running scans periodically. This field is required for Schedule scans.


    Cron string
    Cron schedule for running scans periodically. This field is required for Schedule scans.


    cron String
    Cron schedule for running scans periodically. This field is required for Schedule scans.


    cron string
    Cron schedule for running scans periodically. This field is required for Schedule scans.


    cron str
    Cron schedule for running scans periodically. This field is required for Schedule scans.


    cron String
    Cron schedule for running scans periodically. This field is required for Schedule scans.


    DatascanExecutionStatus, DatascanExecutionStatusArgs

    LatestJobEndTime string
    (Output) The time when the latest DataScanJob started.
    LatestJobStartTime string
    (Output) The time when the latest DataScanJob ended.
    LatestJobEndTime string
    (Output) The time when the latest DataScanJob started.
    LatestJobStartTime string
    (Output) The time when the latest DataScanJob ended.
    latestJobEndTime String
    (Output) The time when the latest DataScanJob started.
    latestJobStartTime String
    (Output) The time when the latest DataScanJob ended.
    latestJobEndTime string
    (Output) The time when the latest DataScanJob started.
    latestJobStartTime string
    (Output) The time when the latest DataScanJob ended.
    latest_job_end_time str
    (Output) The time when the latest DataScanJob started.
    latest_job_start_time str
    (Output) The time when the latest DataScanJob ended.
    latestJobEndTime String
    (Output) The time when the latest DataScanJob started.
    latestJobStartTime String
    (Output) The time when the latest DataScanJob ended.

    Import

    Datascan can be imported using any of these accepted formats:

    • projects/{{project}}/locations/{{location}}/dataScans/{{data_scan_id}}

    • {{project}}/{{location}}/{{data_scan_id}}

    • {{location}}/{{data_scan_id}}

    • {{data_scan_id}}

    When using the pulumi import command, Datascan can be imported using one of the formats above. For example:

    $ pulumi import gcp:dataplex/datascan:Datascan default projects/{{project}}/locations/{{location}}/dataScans/{{data_scan_id}}
    
    $ pulumi import gcp:dataplex/datascan:Datascan default {{project}}/{{location}}/{{data_scan_id}}
    
    $ pulumi import gcp:dataplex/datascan:Datascan default {{location}}/{{data_scan_id}}
    
    $ pulumi import gcp:dataplex/datascan:Datascan default {{data_scan_id}}
    

    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 v7.27.0 published on Thursday, Jun 13, 2024 by Pulumi